Methods and systems for a distributed control system with supplemental attitude adjustment

ABSTRACT

A distributed control system with supplemental attitude adjustment including an aircraft control having an engaged state and a disengaged state. The system also including a plurality of flight components and a plurality of aircraft components communicatively connected to the plurality of flight components, wherein each aircraft component is configured to receive an aircraft command and generate a response command directing the flight components as a function of supplemental attitude. The supplemental attitude based at least in part on the engagement datum and generating a supplemental attitude includes choosing a position supplemental attitude if the aircraft control is disengaged and choosing a velocity supplemental attitude if the aircraft control is engaged. In generating the response command, the aircraft attitude is combined with the supplemental attitude to obtain an aggregate attitude, and the aircraft component is configured to generate the response command based on the aggregate attitude.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of Non-provisional application Ser.No. 17/526,499 filed on Nov. 15, 2021 and entitled “METHODS AND SYSTEMSFOR A DISTRIBUTED CONTROL SYSTEM WITH SUPPLEMENTAL ATTITUDE ADJUSTMENT,”the entirety of which is incorporated herein by reference.

FIELD OF THE INVENTION

The present invention generally relates to the field of distributedaircraft control systems. In particular, the present invention isdirected to methods and systems for a distributed control system withsupplemental attitude adjustment.

BACKGROUND

Aircraft are frequently subject to drift due to wind or sensor noise.This drift can cause the aircraft to deviate from the pilot's intendedflight path. This makes the aircraft more difficult and less precise tocontrol. Additionally, many modern aircraft use fly-by-wire systems tocontrol the aircraft. The failure of these systems can be catastrophic,yet, they can fail even with a single point of failure. Thus, a solutionis needed to compensate for the drift experienced by aircraft and toprovide a more robust and failure resistant fly-by-wire system.

SUMMARY OF THE DISCLOSURE

In an aspect, a distributed control system with supplemental attitudeadjustment includes an aircraft control, the aircraft control locatedwithin an aircraft having an aircraft attitude, a plurality of flightcomponents located within an aircraft having an aircraft attitude, aplurality of aircraft components communicatively connected to theplurality of flight components, wherein each aircraft component of theplurality of aircraft components is configured to receive, from acommand sensor attached to the aircraft control, an aircraft command andgenerate a response command directing the flight components as afunction of an aggregate attitude, wherein the aggregate attitudecombines a supplemental attitude with the aircraft attitude.

In another aspect, a method of distributed control with supplementalattitude adjustment includes receiving, by a plurality of aircraftcomponents communicatively connected to a plurality of flightcomponents, the plurality of aircraft components and the plurality offlight components located within an aircraft having an aircraftattitude, an aircraft command, wherein the aircraft command is receivedfrom a command sensor attached to an aircraft control, generating, bythe plurality of aircraft components, a response command directing theflight components as a function of an aggregate attitude, wherein theaggregate attitude combines a supplemental attitude with the aircraftattitude.

These and other aspects and features of non-limiting embodiments of thepresent invention will become apparent to those skilled in the art uponreview of the following description of specific non-limiting embodimentsof the invention in conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

For the purpose of illustrating the invention, the drawings show aspectsof one or more embodiments of the invention. However, it should beunderstood that the present invention is not limited to the precisearrangements and instrumentalities shown in the drawings, wherein:

FIG. 1 is a diagram of an exemplary embodiment of a system fordistributed control of an aircraft;

FIG. 2 is a diagram of the range of inputs that may be received by anaircraft control;

FIG. 3 is a diagram of an aircraft subject to drift that is parallel toits flight path;

FIG. 4 is a diagram of an aircraft subject to drift that isperpendicular to its flight path;

FIG. 5 is a head-on depiction of a hovering aircraft subject to drift;

FIG. 6 is a diagram of a distributed supplemental attitude controlsystem;

FIG. 7 is a diagrammatic representation of an exemplary embodiment of anaircraft;

FIG. 8 is a flow chart of a method distributed control with supplementalattitude adjustment;

FIG. 9 is a block diagram of an exemplary embodiment of a flightcontroller;

FIG. 10 is a block diagram of an exemplary embodiment of amachine-learning module; and

FIG. 11 is a block diagram of a computing system that can be used toimplement any one or more of the methodologies disclosed herein and anyone or more portions thereof.

The drawings are not necessarily to scale and may be illustrated byphantom lines, diagrammatic representations and fragmentary views. Incertain instances, details that are not necessary for an understandingof the embodiments or that render other details difficult to perceivemay have been omitted.

DETAILED DESCRIPTION

In the following description, for the purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of the present invention. It will be apparent, however,that the present invention may be practiced without these specificdetails. As used herein, the word “exemplary” or “illustrative” means“serving as an example, instance, or illustration.” Any implementationdescribed herein as “exemplary” or “illustrative” is not necessarily tobe construed as preferred or advantageous over other implementations.All of the implementations described below are exemplary implementationsprovided to enable persons skilled in the art to make or use theembodiments of the disclosure and are not intended to limit the scope ofthe disclosure, which is defined by the claims. For purposes ofdescription herein, the terms “upper”, “lower”, “left”, “rear”, “right”,“front”, “vertical”, “horizontal”, and derivatives thereof shall relateto the invention as oriented in FIG. 7 . Furthermore, there is nointention to be bound by any expressed or implied theory presented inthe preceding technical field, background, brief summary or thefollowing detailed description. It is also to be understood that thespecific devices and processes illustrated in the attached drawings, anddescribed in the following specification, are simply exemplaryembodiments of the inventive concepts defined in the appended claims.Hence, specific dimensions and other physical characteristics relatingto the embodiments disclosed herein are not to be considered aslimiting, unless the claims expressly state otherwise.

At a high level, aspects of the present disclosure are directed tosystems and methods for a distributed control system that incorporatessupplemental attitude adjustment. In an embodiment, an aircraft controlmay be monitored to see if it is engaged. If the aircraft control isengaged, a velocity based supplemental attitude generator may be used tosupply a supplemental attitude to counteract drift. If the aircraftcontrol is disengaged, a position based supplemental attitude generatormay be used to supply a supplemental attitude to counteract drift.

Aspects of the present disclosure can be used to implement a distributedflight control system. The distributed flight control system is capableof using supplemental attitude adjustment to counteract drift.

Referring now to FIG. 1 , an exemplary embodiment of a system 100 fordistributed control of an aircraft 104 is illustrated. As used in thisdisclosure an “aircraft” vehicle that may fly by gaining support fromthe air. As a non-limiting example, aircraft may include airplanes,helicopters, airships, blimps, gliders, paramotors, and the likethereof. Aircraft 104 may include an electrically powered aircraft. Inembodiments, electrically powered aircraft may be an electric verticaltakeoff and landing (eVTOL) aircraft. Electric aircraft may be capableof rotor-based cruising flight, rotor-based takeoff, rotor-basedlanding, fixed-wing cruising flight, airplane-style takeoff,airplane-style landing, and/or any combination thereof. Rotor-basedflight, as described herein, is where the aircraft generated lift andpropulsion by way of one or more powered rotors coupled with an engine,such as a “quad copter,” multi-rotor helicopter, or other vehicle thatmaintains its lift primarily using downward thrusting propulsors.Fixed-wing flight, as described herein, is where the aircraft is capableof flight using wings and/or foils that generate life caused by theaircraft's forward airspeed and the shape of the wings and/or foils,such as airplane-style flight.

Still referring to FIG. 1 , system 100 includes a flight component 108.In some embodiments, system 100 may include a plurality of flightcomponents 108. As used in this disclosure a “flight component” is acomponent that promotes flight and guidance of an aircraft. In anembodiment, flight component 108 may be mechanically coupled and/orattached to aircraft 104. As used herein, a person of ordinary skill inthe art would understand “mechanically coupled” to mean that at least aportion of a device, component, or circuit is connected to at least aportion of the aircraft via a mechanical coupling. Said mechanicalcoupling can include, for example, rigid coupling, such as beamcoupling, bellows coupling, bushed pin coupling, constant velocity,split-muff coupling, diaphragm coupling, disc coupling, donut coupling,elastic coupling, flexible coupling, fluid coupling, gear coupling, gridcoupling, hirth joints, hydrodynamic coupling, jaw coupling, magneticcoupling, Oldham coupling, sleeve coupling, tapered shaft lock, twinspring coupling, rag joint coupling, universal joints, or anycombination thereof. As used in this disclosure an “aircraft” is vehiclethat may fly by gaining support from the air. Furthermore, in anembodiment, mechanical coupling may be used to join two pieces ofrotating electric aircraft components.

With continued reference to FIG. 1 , the plurality of flight components108 may be configured to produce a torque. As used in this disclosure a“torque” is a measure of force that causes an object to rotate about anaxis in a direction. For example, and without limitation, torque mayrotate an aileron and/or rudder to generate a force that may adjustand/or affect altitude, airspeed velocity, groundspeed velocity,direction during flight, and/or thrust. For example, plurality of flightcomponents 108 may include a component used to produce a torque thataffects the aircrafts' roll and pitch which may comprise one or moreailerons, defined herein as hinged surfaces which form part of thetrailing edge of each wing in a fixed wing aircraft, and which may bemoved via mechanical means such as without limitation servomotors,mechanical linkages, or the like, to name a few. As a further example,the plurality of flight components 108 may include a rudder, which mayinclude, without limitation, a segmented rudder that produces a torqueabout a vertical axis. Additionally or alternatively, the plurality offlight components 108 may include other flight control surfaces such aspropulsors, rotating flight controls, or any other structural featureswhich can adjust the movement of the aircraft, wherein propulsors mayinclude one or more puller components and/or pusher components asdescribed below in detail, in reference to FIG. 2 . Plurality of flightcomponents 108 may include one or more rotors, turbines, ducted fans,paddle wheels, and/or other components configured to propel a vehiclethrough a fluid medium including, but not limited to air.

In another embodiment, and still referring to FIG. 1 , propulsor mayinclude a propeller, a blade, or any combination of the two. Thefunction of a propeller is to convert rotary motion from an engine orother power source into a swirling slipstream which pushes the propellerforwards or backwards. Propulsor may include a rotating power-drivenhub, to which are attached several radial airfoil-section blades suchthat the whole assembly rotates about a longitudinal axis. As anon-limiting example, the blade pitch of the propellers may be fixed ata fixed angle, manually variable to a few set positions, automaticallyvariable (e.g. a “constant-speed” type), and/or any combination thereofas described further above. As used in this disclosure a “fixed angle”is an angle that is secured and/or unmovable from the attachment point.For example, and without limitation, a fixed angle may be an angle of2.2° inward and/or 1.7° forward. As a further non-limiting example, afixed angle may be an angle of 3.6° outward and/or 2.7° backward. In anembodiment, propellers for an aircraft are designed to be fixed to theirhub at an angle similar to the thread on a screw makes an angle to theshaft; this angle may be referred to as a pitch or pitch angle whichwill determine the speed of the forward movement as the blade rotates.Additionally or alternatively, propulsor component may be configured ata variable pitch angle. As used in this disclosure a “variable pitchangle” is an angle that may be moved and/or rotated. For example, andwithout limitation, propulsor component may be angled at a first angleof 3.3° inward, wherein propulsor component may be rotated and/orshifted to a second angle of 1.7° outward.

Still referring to FIG. 1 , propulsor may include a thrust element whichmay be integrated into the propulsor. The thrust element may include,without limitation, a device using moving or rotating foils, such as oneor more rotors, an airscrew or propeller, a set of airscrews orpropellers such as contra-rotating propellers, a moving or flappingwing, or the like. Further, a thrust element, for example, can includewithout limitation a marine propeller or screw, an impeller, a turbine,a pump-jet, a paddle or paddle-based device, or the like.

With continued reference to FIG. 1 , plurality of flight components 108may include power sources, control links to one or more elements, fuses,and/or mechanical couplings used to drive and/or control any otherflight component. Plurality of flight components 108 may include a motorthat operates to move one or more flight control components, to driveone or more propulsors, or the like. A motor may be driven by directcurrent (DC) electric power and may include, without limitation,brushless DC electric motors, switched reluctance motors, inductionmotors, or any combination thereof. A motor may also include electronicspeed controllers or other components for regulating motor speed,rotation direction, and/or dynamic braking.

Still referring to FIG. 1 , plurality of flight components 108 mayinclude an energy source. An energy source may include, for example, agenerator, a photovoltaic device, a fuel cell such as a hydrogen fuelcell, direct methanol fuel cell, and/or solid oxide fuel cell, anelectric energy storage device (e.g. a capacitor, an inductor, and/or abattery). An energy source may also include a battery cell, or aplurality of battery cells connected in series into a module and eachmodule connected in series or in parallel with other modules.Configuration of an energy source containing connected modules may bedesigned to meet an energy or power requirement and may be designed tofit within a designated footprint in an electric aircraft in whichsystem 100 may be incorporated.

In an embodiment, and still referring to FIG. 1 , an energy source maybe used to provide a steady supply of electrical power to a load overthe course of a flight by a vehicle or other electric aircraft. Forexample, the energy source may be capable of providing sufficient powerfor “cruising” and other relatively low-energy phases of flight. Anenergy source may also be capable of providing electrical power for somehigher-power phases of flight as well, particularly when the energysource is at a high SOC, as may be the case for instance during takeoff.In an embodiment, the energy source may be capable of providingsufficient electrical power for auxiliary loads including withoutlimitation, lighting, navigation, communications, de-icing, steering orother systems requiring power or energy. Further, the energy source maybe capable of providing sufficient power for controlled descent andlanding protocols, including, without limitation, hovering descent orrunway landing. As used herein the energy source may have high powerdensity where the electrical power an energy source can usefully produceper unit of volume and/or mass is relatively high. The electrical poweris defined as the rate of electrical energy per unit time. An energysource may include a device for which power that may be produced perunit of volume and/or mass has been optimized, at the expense of themaximal total specific energy density or power capacity, during design.Non-limiting examples of items that may be used as at least an energysource may include batteries used for starting applications including Liion batteries which may include NCA, NMC, Lithium iron phosphate(LiFePO4) and Lithium Manganese Oxide (LMO) batteries, which may bemixed with another cathode chemistry to provide more specific power ifthe application requires Li metal batteries, which have a lithium metalanode that provides high power on demand, Li ion batteries that have asilicon or titanite anode, energy source may be used, in an embodiment,to provide electrical power to an electric aircraft or drone, such as anelectric aircraft vehicle, during moments requiring high rates of poweroutput, including without limitation takeoff, landing, thermal de-icingand situations requiring greater power output for reasons of stability,such as high turbulence situations, as described in further detailbelow. A battery may include, without limitation a battery using nickelbased chemistries such as nickel cadmium or nickel metal hydride, abattery using lithium ion battery chemistries such as a nickel cobaltaluminum (NCA), nickel manganese cobalt (NMC), lithium iron phosphate(LiFePO4), lithium cobalt oxide (LCO), and/or lithium manganese oxide(LMO), a battery using lithium polymer technology, lead-based batteriessuch as without limitation lead acid batteries, metal-air batteries, orany other suitable battery. Persons skilled in the art, upon reviewingthe entirety of this disclosure, will be aware of various devices ofcomponents that may be used as an energy source.

Still referring to FIG. 1 , an energy source may include a plurality ofenergy sources, referred to herein as a module of energy sources. Themodule may include batteries connected in parallel or in series or aplurality of modules connected either in series or in parallel designedto deliver both the power and energy requirements of the application.Connecting batteries in series may increase the voltage of at least anenergy source which may provide more power on demand. High voltagebatteries may require cell matching when high peak load is needed. Asmore cells are connected in strings, there may exist the possibility ofone cell failing which may increase resistance in the module and reducethe overall power output as the voltage of the module may decrease as aresult of that failing cell. Connecting batteries in parallel mayincrease total current capacity by decreasing total resistance, and italso may increase overall amp-hour capacity. The overall energy andpower outputs of at least an energy source may be based on theindividual battery cell performance or an extrapolation based on themeasurement of at least an electrical parameter. In an embodiment wherethe energy source includes a plurality of battery cells, the overallpower output capacity may be dependent on the electrical parameters ofeach individual cell. If one cell experiences high self-discharge duringdemand, power drawn from at least an energy source may be decreased toavoid damage to the weakest cell. The energy source may further include,without limitation, wiring, conduit, housing, cooling system and batterymanagement system. Persons skilled in the art will be aware, afterreviewing the entirety of this disclosure, of many different componentsof an energy source.

Still referring to FIG. 1 , an aircraft control 112 is located withinsystem 100. As used in this disclosure an “aircraft control” is acontrol and/or guidance system that maneuvers the aircraft. In anembodiment, aircraft control 112 may include a mechanical and/ormanually operated flight control system. For example, and withoutlimitation aircraft control 112 may include a collective control. Asused in this disclosure a “collective control” is a mechanical controlof an aircraft that allows a pilot and/or other operator to adjustand/or control the pitch angle of aircraft 104. For example and withoutlimitation, collective control may alter and/or adjust a pitch angle ofall the main rotor blades collectively. For example, and withoutlimitation aircraft control 112 may include a yoke control. As used inthis disclosure a “yoke control” is a mechanical control of an aircraftto control the pitch and/or roll. For example and without limitation,yoke control may alter and/or adjust the roll angle of aircraft 104 as afunction of controlling and/or maneuvering ailerons. In an embodiment,aircraft control 112 may include one or more foot brakes, controlsticks, pedals, throttle levels, and the like thereof. Additionally oralternatively, aircraft control 112 may be configured to translate adesired command. As used in this disclosure a “desired command” is adirection and/or command that a pilot desires, wishes, and/or wants fora flight component. In an embodiment, and without limitation, desiredcommand may include a desired torque for flight component 108. Forexample, and without limitation, aircraft control 112 may translate thata desired torque for a propeller be 160 lb. ft. of torque. As a furthernon-limiting example, aircraft control 112 may translate that a pilot'sdesired torque for a propulsor be 290 lb. ft. of torque. In anotherembodiment, aircraft control 112 may include a digital and/or automatedflight control system. For example, and without limitation, aircraftcontrol 112 may include a computing device and/or flight controllercapable of producing an autonomous function, wherein an autonomousfunction is described below in detail, in reference to FIG. 4 . In anembodiment, aircraft control 112 may include storing a flight planand/or flight path. For example, and without limitation, aircraftcontrol 112 may store a flight plan in a localized memory and/or memorycache of a first aircraft component, wherein a plurality of segments ofthe flight plan may be stored in a plurality of aircraft components ofaircraft 104, wherein an aircraft component is described below indetail. In some embodiments, aircraft control 112 may be a joystick. Forthe purposes of this disclosure, a “joystick” is a control systemincluding a stick that pivots on its base and reports on the angle orposition of the stick.

Still referring to FIG. 1 , system 100 includes an aircraft component116 attached to flight component 108 of the plurality of flightcomponents. As used in this disclosure an “aircraft component” is alogic circuit communicatively connected to a flight component, that maybe configured to perform steps and/or actions as described in furtherdetail below. “Communicatively connected,” for the purpose of thisdisclosure, means connected such that data can be transmitted, whetherwirelessly or wired. In an embodiment, and without limitation, aircraftcomponent may include one or more application-specific integratedcircuits (ASICs), field-programmable gate arrays (FPGAs), multiplexors,registers, arithmetic logic units (ALUs), computer memory caches,microprocessors, computing devices, and the like thereof. In anembodiment, system 100 may include a plurality of aircraft components116. Aircraft component 116 may include any computing device asdescribed in this disclosure, including without limitation amicrocontroller, digital signal processor (DSP) and/or system on a chip(SoC) as described in this disclosure. Computing device may include, beincluded in, and/or communicate with a mobile device such as a mobiletelephone or smartphone. Aircraft component 116 may include a singlecomputing device operating independently, or may include two or morecomputing device operating in concert, in parallel, sequentially or thelike; two or more computing devices may be included together in a singlecomputing device or in two or more computing devices. Aircraft component116 may interface or communicate with one or more additional devices asdescribed below in further detail via a network interface device.Network interface device may be utilized for connecting aircraftcomponent 116 to one or more of a variety of networks, and one or moredevices. Examples of a network interface device include, but are notlimited to, a network interface card (e.g., a mobile network interfacecard, a LAN card), a modem, and any combination thereof. Examples of anetwork include, but are not limited to, a wide area network (e.g., theInternet, an enterprise network), a local area network (e.g., a networkassociated with an office, a building, a campus or other relativelysmall geographic space), a telephone network, a data network associatedwith a telephone/voice provider (e.g., a mobile communications providerdata and/or voice network), a direct connection between two computingdevices, and any combinations thereof. A network may employ a wiredand/or a wireless mode of communication. In general, any networktopology may be used. Information (e.g., data, software etc.) may becommunicated to and/or from a computer and/or a computing device.Aircraft component 116 may include but is not limited to, for example, acomputing device or cluster of computing devices in a first location anda second computing device or cluster of computing devices in a secondlocation. Aircraft component 116 may include one or more computingdevices dedicated to data storage, security, distribution of traffic forload balancing, and the like. Aircraft component 116 may distribute oneor more computing tasks as described below across a plurality ofcomputing devices of computing device, which may operate in parallel, inseries, redundantly, or in any other manner used for distribution oftasks or memory between computing devices. Aircraft component 116 may beimplemented using a “shared nothing” architecture in which data iscached at the worker, in an embodiment, this may enable scalability ofsystem 100 and/or computing device.

With continued reference to FIG. 1 , aircraft component 116 may bedesigned and/or configured to perform any method, method step, orsequence of method steps in any embodiment described in this disclosure,in any order and with any degree of repetition. For instance, aircraftcomponent 116 may be configured to perform a single step or sequencerepeatedly until a desired or commanded outcome is achieved; repetitionof a step or a sequence of steps may be performed iteratively and/orrecursively using outputs of previous repetitions as inputs tosubsequent repetitions, aggregating inputs and/or outputs of repetitionsto produce an aggregate result, reduction or decrement of one or morevariables such as global variables, and/or division of a largerprocessing task into a set of iteratively addressed smaller processingtasks. Aircraft component 116 may perform any step or sequence of stepsas described in this disclosure in parallel, such as simultaneouslyand/or substantially simultaneously performing a step two or more timesusing two or more parallel threads, processor cores, or the like;division of tasks between parallel threads and/or processes may beperformed according to any protocol suitable for division of tasksbetween iterations. Persons skilled in the art, upon reviewing theentirety of this disclosure, will be aware of various ways in whichsteps, sequences of steps, processing tasks, and/or data may besubdivided, shared, or otherwise dealt with using iteration, recursion,and/or parallel processing.

Still referring to FIG. 1 , aircraft component 116 is configured toreceive an aircraft command. As used in this disclosure an “aircraftcommand” is a command directing a flight component to perform an actionand/or motion. However, in some embodiments, flight component mayreceive an aircraft command from a flight controller. In an embodiment,and without limitation, aircraft command may include a command toincrease and/or enhance a thrust force generated by a propulsor toprovide lift to aircraft 104. For example, and without limitation,aircraft command may instruct a propeller to increase a firstrevolutions per minute of 2,000 to a second revolutions per minute of4,000. In an embodiment, and without limitation, aircraft command mayinclude a command to alter and/or shift about an axis. For example, andwithout limitation, aircraft command may include a command to rotate arudder 3° about a vertical axis. In another embodiment, and withoutlimitation, aircraft command may include a command to reduce and/orreverse a first torque magnitude and/or direction. As a non-limitingexample, aircraft command may command a propeller that has a firsttorque of 12 Nm to reduce the torque to 2 Nm. In an embodiment, andwithout limitation, aircraft command may include one or more commands todirect a flight component to alter a heading, speed, altitude, departureangle, approach angle, route paths, and the like thereof.

Still referring to FIG. 1 , aircraft component 116 is configured toreceive aircraft command from a command sensor 120 attached to aircraftcontrol 112. As used in this disclosure a “command sensor” is a device,module, and/or subsystem, utilizing any hardware, software, and/or anycombination thereof to detect events and/or changes to aircraft 104 as afunction aircraft control 112. For example, and without limitation,command sensor may detect events as a function of one or moremodifications of aircraft control 112, modifications compared to aflight plan, and the like thereof. For example, and without limitation,command sensor 120 may be configured to detect one or more changes intorque, force, thrust, pitch angle, angle of attack, velocity, momentum,altitude, roll, yaw, and the like thereof. In an embodiment, and withoutlimitation, command sensor 120 may be attached via a mechanically and/orcommunicatively connected, as described above, to aircraft 104.Additionally or alternatively, command sensor 120 may be configured todetect aircraft command, wherein aircraft command includes a desiredoutput of flight component 108 of the plurality of flight components. Asused in this disclosure a “desired output” is an output and/or functionthat is wanted and/or expected to be performed by flight component 108.For example, and without limitation, desired output may denote that apropeller blade should maintain a rotational velocity of 330 rad/s. As afurther non-limiting example, desired output may denote that aircraft104 should have a pitch angle of 3.7° . As a further non-limitingexample, desired output may denote that aircraft 104 should maintain aforward thrust of 800 N. In an embodiment, and without limitation,command sensor 120 may transmit the aircraft command to aircraftcomponent 116. For example, command sensor 120 may transmit aircraftcommand to aircraft component 116 as a function of one or morecommunication signals and/or signal codes as described below in detail.As a further non-limiting example, command sensor 120 may transmitaircraft command by converting the aircraft command to a digitalelectronic signal. As used in this disclosure a “digital electronicsignal” is a coded electrical impulse to convey information. As anon-limiting example, digital electronic signal may include a bit thatspecific a basic unit of information that may be represented using termsand/or symbols such as 1, 0, yes, no, true, false, +, −, on, and/or off.

Still referring to FIG. 1 , aircraft component 116 is configured toreceive an engagement datum from the command sensor 120. An “engagementdatum” is a piece of data that indicates whether aircraft control 112 isengaged. In some embodiments, engagement datum may be a “0” or a “1.” Asa non-limiting example, the engagement datum may be “1” when aircraftcontrol 112 is engaged. Additionally, as a non-limiting example, theengagement datum may be “0” when aircraft control 112 is disengaged.Aircraft control 112 may be disengaged, for example, when aircraftcontrol 112 is detected to be at its default position. In anotherembodiment, aircraft control 112 may be disengaged when aircraft control112 is detected to be within a first threshold from its defaultposition. As a non-limiting example a joystick is generallyspring-centered, so that, when the joystick is not disengaged, itreturns to a vertical position. Aircraft control 112 may be detected tobe engaged when aircraft control 112 is detected to be outside of asecond threshold from its default position. In some embodiments, firsttolerance amount may be different from each other. In other embodiments,first tolerance amount may be equal to second tolerance amount. Firstand second tolerance amount may be numerical measurements, or they maybe expressed as percentages.

In another embodiment, and still referring to FIG. 1 , command sensor120 may be configured to detect one or more statuses of aircraft 104 asa function of aircraft control 112. For example and without limitation,a status of aircraft 104 may include datum representing one or moreconditions of the energy source and/or motor. One or more conditions mayinclude, without limitation, voltage levels, electromotive force,current levels, temperature, current speed of rotation, and the like.Command sensor 120 may further include detecting electrical parameters.Electrical parameters may include, without limitation, voltage, current,ohmic resistance of a flight component. Command sensor 120 may includeone or more environmental sensors, which may function to senseparameters of the environment surrounding the aircraft. An environmentalsensor may include without limitation one or more sensors used to detectambient temperature, barometric pressure, and/or air velocity, one ormore motion sensors which may include without limitation gyroscopes,accelerometers, inertial measurement unit (IMU), and/or magneticsensors, one or more humidity sensors, one or more oxygen sensors, orthe like. Additionally or alternatively, command sensor 120 may includeat least a geospatial sensor. Command sensor 120 may be located insidean aircraft; and/or be included in and/or attached to at least a portionof the aircraft. Command sensor 120 may include one or more proximitysensors, displacement sensors, vibration sensors, and the like thereof.Command sensor 120 may be comprised of one or more gyroscopes,accelerometers, magnetometers, inertial measurement units, pressuresensors. Command sensor 120 may be used to monitor the status ofaircraft 104 for both critical and non-critical functions. Commandsensor 120 may be incorporated into vehicle or aircraft or be remote.

With continued reference to FIG. 1 , in some embodiments, command sensor120 may be communicatively connected to an aircraft control component.Aircraft control component may be configured to calculate thedisplacement of the aircraft control 112 from a default position,compare the displacement of the aircraft control 112 against the firstthreshold, and transmit an engagement datum to a command sensor 120 toindicate whether aircraft control 112 is engaged or disengaged. In someembodiments, aircraft control component may compare the displacement ofthe aircraft control 112 against the second threshold. Aircraft controlcomponent may be configured to perform steps and/or actions as describedin further detail below. In an embodiment, and without limitation,aircraft control component may include or more application-specificintegrated circuits (ASICs), field-programmable gate arrays (FPGAs),multiplexors, registers, arithmetic logic units (ALUs), computer memorycaches, microprocessors, computing devices, and the like. In anembodiment, system 100 may include a plurality of aircraft controlcomponents. Aircraft control component may include any computing deviceas described in this disclosure.

Still referring to FIG. 1 , aircraft component 116 is configured toobtain, from an attitude sensor 124, an aircraft orientation. As used inthis disclosure an “attitude sensor” is a device, module, and/orsubsystem, utilizing any hardware, software, and/or any combinationthereof to detect an attitude and/or orientation of aircraft 104. Forexample, and without limitation, attitude sensor 124 may include one ormore sensors similar to command sensor 120. In an embodiment, andwithout limitation, attitude sensor 124 may include a proximity sensor,pressure sensor, light sensor, pitot tubes, air speed sensor, and thelike thereof. For example, attitude sensor 124 may include a motionsensor configured to detect motion in three or more dimensions and/ororientation in three dimensions of aircraft 104. For example, andwithout limitation, a motion sensor may include a MEMS sensor, inertialmeasurement unit (IMU), an accelerometer, wherein one or moreaccelerometers may include a plurality of accelerometers, such as threeor more accelerometers positioned to span three dimensions of possibleacceleration, so that any direction and magnitude of acceleration inthree dimensions may be detected and measured in three dimensions, andthe like thereof. Attitude sensor 124 may include one or moregyroscopes; one or more gyroscopes may include a plurality ofgyroscopes, such as three or more gyroscopes positioned to span threedimensions of possible acceleration, so that any direction and magnitudeof change in angular position in three dimensions may be detected andmeasured in three dimensions. Attitude sensor 124 may include one ormore magnetic sensors or magnetometers such as Hall effect sensors,compasses such as solid-state compasses, or the like; one or moremagnetometers may include a plurality of magnetometers, such as three ormore magnetometers positioned to span three dimensions of possibleorientation, so that any direction and magnitude of change in magneticfield in three dimensions may be detected and measured in threedimensions, possibly for measurement of the aircraft's orientation tothe Earth's true North or detection of magnetic anomalies.

In an embodiment, and without limitation, attitude sensor 124 mayinclude one or more navigation facility receivers. As used in thisdisclosure a “navigation facility receiver” is sensor and/or receiverthat may locate and/or identify a location of an aircraft with respectto a geolocation. For example and without limitation, navigationfacility receiver may include a global positioning system (GPS)receiver. As a further non-limiting example, navigation facilityreceiver may include a global navigation satellite system (GLONASS)receiver. As a further non-limiting example, navigation facilityreceiver may include a BeiDou receiver. As a further non-limitingexample, navigation facility receiver may include a Galileo receiver. Asa further non-limiting example, navigation facility may include a NAVICreceiver. In an embodiment, navigation facility receiver may include oneor more satellite constellation receivers and/or similar emittingsystems that can calculate a location based on the time and/or phasedifference of the receiver signals. In an embodiment, and withoutlimitation, navigation facility receiver may include a receivingantenna, accompanying circuits, and processing. One or more navigationfacility receivers may be configured to determine the orientation of theaircraft in relation to the Earth's true North, using differential GPS,phase differences, and/or other methods to exploit the satelliteconstellations and their positions. One or more facility navigationreceivers may be configured to receive and determine the local timebased on the time information received from the satellite signals. Oneor more navigation facility receivers may receive position and timingsignals, and the like and convert such detected signals into electricalsignals, which may be processed further by aircraft component 116.

In an embodiment, and still referring to FIG. 1 , attitude sensor 124may detect a topographical datum. As used in this disclosure a“topographical datum” is an element of datum representing thearrangement and/or location of a physical feature of a geolocation. Forexample, and without limitation, topographical datum may include one ormore elements of datum denoting a mountain range, skyscraper, river,ridge, ocean, lake, vehicle, animal, person, street, field, tree, andthe like thereof. In an embodiment, and without limitation, attitudesensor 124 may include a light radar component. As used in thisdisclosure a “light radar component” is an active imaging source thattransmits light toward an object or field of interest and detectsback-scattered or reflected light, measuring time of flight (ToF),interferometry, and/or phase of such back-scattered and/or reflectedlight to compute distances to, velocities, and/or accelerations ofobjects at points from which back-scatter and/or reflection occurred. Inan embodiment, the wavelength of light may be outside the range ofvisible light; for instance, and without limitation, wavelength may bein the infrared range as described above. Light radar component mayinclude a “flash lidar” component, mechanical or non-mechanical beamsteering, light patterns, and/or computational imaging methods, such asplenoptic or other multi-aperture embodiments. In an embodiment, andwithout limitation, light radar component may include one or moreoptical elements for focusing, collimating, and/or transmitting lightemitted by light source. In an embodiment, intensity and/or focus maydefault to minimally harmful settings, permitting allowing ToF rangingor the like to determine a distance to a nearest topographical datapoint and/or ground point. Light radar component may include detectorsthat may be sensitive specifically to a narrow band of wavelengthstransmitted by light source, and/or may be sensitive to a range ofwavelengths that includes the band transmitted by the light source.Detectors may be designed to react quickly to initial detection ofphotons, for instance through use of APDs or other highly sensitivedetectors. Still referring to FIG. 1 , an “aircraft orientation,” asused herein, is an aircraft attitude about a three-axis system. As usedin this disclosure a “three-axis system” is region of space representedby three dimensions that share a similar origin. For example, andwithout limitation, three-axis system may include a more yaw, pitch,and/or roll axis. As used in this disclosure a “yaw axis” is an axisthat is directed towards the bottom of the aircraft, perpendicular tothe wings. For example, and without limitation, a positive yawing motionmay include adjusting and/or shifting the nose of aircraft 104 to theright about the vertical axis. As used in this disclosure a “pitch axis”is an axis that is directed towards the right laterally extending wingof the aircraft. For example, and without limitation, a positivepitching motion may include adjusting and/or shifting the nose ofaircraft 104 upwards about the horizontal axis. As used in thisdisclosure a “roll axis” is an axis that is directed longitudinallytowards the nose of the aircraft, parallel to the fuselage. For example,and without limitation, a positive rolling motion may include liftingthe left and lowering the right wing concurrently about the longitudinalaxis. Additionally or alternatively, attitude sensor 124 may detectaircraft orientation and transmit aircraft orientation to aircraftcomponent 116. For example, attitude sensor 124 may transmit aircraftorientation to aircraft component 116 as a function of one or morecommunication signals and/or signal codes as described below in detail.As a further non-limiting example, attitude sensor 124 may transmitaircraft orientation by converting the aircraft orientation to a digitalelectronic signal, wherein a digital electronic signal is a codedelectrical impulse to convey information as described above, in detail.

Still referring to FIG. 1 , aircraft component 116 is configured toreceive an actual velocity from a velocity sensor 128. For the purposesof this disclosure, “velocity” refers to an object rate of movement withrespect to a frame of reference. Velocity is generally expressed as avector, wherein the magnitude of the vector is the speed of the objectand the direction of the vector is the direction of the object'smovement. For the purposes of this disclosure “actual velocity” is thevelocity of the aircraft 104. In some embodiments, velocity sensor 128may include a pitot tube. A pitot tube may be used to measure theaircraft's airspeed. As a non-limiting example, a pitot tube may be atube pointing into the airflow experienced by aircraft 104. As anon-limiting example, a pitot tube may be mounted on the wing ofaircraft 104. As another non-limiting example, the pitot tube may bemounted on the forward end of the aircraft 104 fuselage. The pitot tubecan measure the dynamic pressure of the airflow experienced by theaircraft 104. In some embodiments, velocity sensor 128 may also includea static port. As a non-limiting example, the static port may be a holethat is flush-mounted on the fuselage of aircraft 104. The static portmay be used to measure the static pressure of air. In some embodiments,the velocity sensor 128 may include a Prandtl tube. A Prandtl tube mayalso be called a pitot-static tube. As a non-limiting example, a Prandtltube is essentially a pitot tube, with a second co-axial tube with holeson the sides of the device. This second co-axial tube may measure staticpressure, whereas the pitot tube can measure dynamic pressure.

Still referring to FIG. 1 , velocity sensor 128 may include a sensorconfigured to detect the direction of the aircraft. In some embodiments,velocity sensor 128 may include an angle of attack vane. An angle ofattack vane may be used to measure the difference in angle between theairspeed vector, and a predefined line on an aircraft wing. As anon-limiting example, an angle of attack vane may be used to measure thedifference in angle between the airspeed vector and the chord line ofthe aircraft wing. As a non-limiting example, this measurement mayindicate whether aircraft 104 is ascending or descending in altitude.This may be used as a component in calculating the direction of theaircraft 104 velocity vector. In some embodiments, velocity sensor 128may include a heading sensor. In some embodiments, this heading sensormay be a compass. As a non-limiting example, this compass may indicatethe heading of the aircraft using the cardinal directions. This headingmay be used as a component in calculating the direction of aircraft 104velocity vector. In some embodiments, velocity sensor 128 may include aplurality of different sensors, or velocity sensor 128 may include asensor suite. In some embodiments, velocity sensor may not be a discretesensor or set of sensors, but, instead, may be made up of sensors chosenfrom the on-plane sensors of aircraft 104. In some embodiments, velocitysensor 128 may include a variety of other sensors, such as altimeters,altitude and heading reference systems (AHRS), navigation systems likeGPS, control surface sensors, temperature sensors, pressure sensors,gyroscopes, accelerometers, and the like.

Still referring to FIG. 1 , aircraft component 116 is configured tocommand flight component 108 of the plurality of flight components toproduce a response command. In some embodiments, aircraft component 116may generate a response command and send the response command to flightcomponent 108. Alternatively, in some embodiments, flight component 108may receive an instruction from a flight controller and, as a functionof this command, generate the response command. As used in thisdisclosure a “response command” is a command directing a flightcomponent to perform an action and/or motion as a function of theaircraft command and/or aircraft orientation. In an embodiment, andwithout limitation, response command may include an actuator command. Asused in this disclosure an “actuator command” is a direction and/orinstruction given to an actuator to move and/or shift a flightcomponent. For example, and without limitation, actuator command maydirect an actuator to may adjust a propulsor 4° in the horizontal axis.As a further non, limiting example, actuator command may direct anactuator to may adjust an aileron 2° in the vertical axis. As a furthernon-limiting example, actuator command may direct a flight componentwith a first vertical axis, wherein the first vertical axis may includea 2.2° inward and/or 2.7° forward, to maneuver and/or shift the flightcomponent +/−15 ° in the horizontal and/or longitudinal axis.Additionally or alternatively, response command may include a thrustcommand. As used in this disclosure a “thrust command” is a directionand/or instruction given to a flight component that produces thrust. Forexample, and without limitation, thrust command may instruct a propulsorto reduce a first thrust of 8,000 N to a second thrust of 2,000 N. As afurther non-limiting example, thrust command may instruct a propulsor toincrease an airspeed from a first airspeed of 230 km/h to a secondairspeed of 402 km/h.

Still referring to FIG. 1 , response command may be produced as afunction of determining at least an aircraft response. As used in thisdisclosure an “aircraft response” is one or more actions an aircraft mayperform in response to a change. For example, and without limitation,aircraft response may include decreasing altitude, increasing altitude,reducing airspeed velocity, changing the heading direction, applying abraking force, and the like thereof. In an embodiment, and withoutlimitation, aircraft response may be determined as a function ofsimulating an aircraft command adjustment. As used in this disclosure an“aircraft command adjustment” is a proposed change and/or modificationto aircraft 104 that may elucidate a response. For example, and withoutlimitation, aircraft command adjustment may include a proposed change toshift and/or alter a rudder. As a further non-limiting example, aircraftcommand adjustment may include a proposed change to increase rotationalvelocity of a rotor. In an embodiment, aircraft command adjustment maybe simulated by detecting a failure event. As used in this disclosure a“failure event” is an element of data identifying a failure of a flightcomponent of the plurality of flight components has occurred. In anembodiment and without limitation, failure event may include rotationdegradation. As used in this disclosure “rotation degradation” is areduced function of flight components such that a loss of control occursin one of the axis in the three-axis system. As a non-limiting example,rotation degradation may occur due to a rotor in a quadrotorconfiguration that is not operating at the capacity necessary tomaintain the flight plan, wherein the yaw portion of the torque exertedby the remaining rotors is not eliminated and an uncontrollable yaw axisforce is exerted. In a further embodiment and without limitation,failure event may include a propulsor that is not generating enoughtorque to maintain the flight plan.

In an embodiment, and still referring to FIG. 1 , aircraft commandadjustment may be simulated as a function of a control algorithm. Asused in this disclosure a “control algorithm” is a finite sequence ofwell-defined computer implementable instructions that may determine theflight component of the plurality of flight components to be adjusted.For example, and without limitation, control algorithm may include oneor more algorithms that reduce and/or prevent aviation asymmetry. As afurther non-limiting example, control algorithms may include one or moremodels generated as a function of a software including, but not limitedto Simulink by MathWorks, Natick, Mass., USA. In an embodiment, andwithout limitation, aircraft component may simulate one or moreadjustments independent of the plurality of second aircraft components.In another embodiment, and without limitation, aircraft component maysimulate one or more adjustments in conjunction with the simulationperformed by the plurality of second aircraft components. In anembodiment, and without limitation, control algorithm may be configuredto generate an auto-code, wherein an “auto-code,” is used herein, is acode and/or algorithm that is generated as a function of the one or moremodels and/or software's. In another embodiment, control algorithm maybe configured to receive a segmented control algorithm. As used in thisdisclosure a “segmented control algorithm” is control algorithm that hasbeen separated and/or parsed into discrete sections. For example, andwithout limitation, segmented control algorithm may include a parsedcontrol algorithm into two or more segments, wherein each segment ofcontrol algorithm may be performed by one or more aircraft componentsoperating on distinct flight components.

In an embodiment, and still referring to FIG. 1 , control algorithm maybe configured to determine a segmentation boundary as a function ofsegmented control algorithm. As used in this disclosure a “segmentationboundary” is a limit and/or delineation associated with the segments ofthe segmented control algorithm. For example, and without limitation,segmentation boundary may denote that a segment in the control algorithmhas a first starting section and/or a first ending section. As a furthernon-limiting example, segmentation boundary may include one or moreboundaries associated with an ability of flight component 108. In anembodiment, control algorithm may be configured to create an optimizedsignal communication as a function of segmentation boundary. As used inthis disclosure an “optimized signal communication” is an optimizeddiscrete timing of signal communications. For example, and withoutlimitation, optimized signal communication may include identifying thediscrete timing required to transmit and/or receive the one or moresegmentation boundaries. For example, and without limitation optimizedsignal communication may determine one or more discrete timings to allowfor separation of code across communication networks and/or aircraftcomponents attached to the plurality of flight components.

The communication network may be consistent with any communicationnetwork disclosed in U.S. App. Ser. No. 17/323,637, filed on May 18,2021, and entitled “SYSTEM AND METHOD FOR DISTRIBUTED CONTROL OF ANAIRCRAFT,” the entirety of which is hereby incorporated by reference.

In an embodiment, and still referring to FIG. 1 , determining the atleast an aircraft response may include receiving a first aircraftcommand from command sensor 120 attached to aircraft control 112,wherein a first aircraft command may include any of the aircraft commandas described above. In an embodiment, and without limitation, aircraftcomponent 116 may obtain from a related flight component of theplurality of flight components an adjustment impact, wherein a relatedflight component is a second flight component that is distinct from afirst flight component. For example, and without limitation, a firstflight component may include a propulsor, wherein a second flightcomponent may include a rotor and/or aileron. As used in this disclosurean “adjustment impact” is an effect and/or impact that a change toflight component 108 may have on a related flight component. Forexample, and without limitation, an adjustment impact may denote that areduction of torque to a first propulsor may result in an overproductionof torque on a second propulsor. As a further non-limiting example,adjustment impact may denote that a shift of an aileron may result in atorque exerted on the rudder. In an embodiment, and without limitationaircraft component 116 may determine the at least aircraft response as afunction of the first aircraft command and the adjustment impact.

Still referring to FIG. 1 , system 100 may be configured to include acommunication network that allows the aircraft component 116 attached toflight component 108 to communicate with an second aircraft componentattached to an alternate flight component, wherein a communicationnetwork is a pattern and/or direction in which data and/or signals mayflow in system 100. As used in this disclosure an “second aircraftcomponent” is an aircraft component that is different and/or distinctfrom a first aircraft component. As used in this disclosure an“alternate flight component” is a flight component that is differentand/or distinct from a first flight component. For example, and withoutlimitation, an aircraft component attached to a rotor may communicate toan second aircraft component attached to an aileron. As a furthernon-limiting example, an aircraft component attached to a rudder maycommunicate to an second aircraft component of a rotor. In anembodiment, aircraft component 116 may communicate with a plurality ofsecond aircraft components as a function of the communication network.As a non-limiting embodiment, flight component may send an outgoingsignal to an alternate flight component using the above-mentionedcommunication network. For example, and without limitation, aircraftcomponent may communicate with the plurality of second aircraftcomponents as a function of one or more chain paths, all-channel paths,and/or neural networks that assign a weighted value to a transmitteddatum. As a further non-limiting example, aircraft component maycommunicate with the plurality of second aircraft components as afunction of cooperative processing, parallel processing, and the likethereof. In an embodiment, and without limitation, aircraft component116 may communicate with an second aircraft component of the pluralityof second aircraft components as a function of a wired protocol. As anon-limiting example, aircraft component 116 may communicate with analternate flight component of the plurality of alternate flightcomponents as a function of a master bus controller, universalasynchronous receiver-transmitters (UART), universal serial buses(USBs), bus architectures, and the like thereof. In another embodiment,and without limitation, aircraft component 116 may communicate with ansecond aircraft component of the plurality of second aircraft componentsas a function of a wireless protocol. For example, and withoutlimitation, aircraft component 116 may communicate with an alternateflight component of the plurality of alternate flight components as afunction of a communication using radio waves, electric fields, mobilebroadband, Wi-Fi, and/or the BLUETOOTH protocol promulgated by BluetoothSIG, Inc. of Kirkland, Washington, wherein Bluetooth is a wirelesstechnology used for exchanging data between devices over short distancesusing ultra high frequency radio waves between 2.402 GHz to 2.480 GHz.

In an embodiment, and still referring to FIG. 1 , aircraft component 116may receive an alternate aircraft command from the second aircraftcomponent. As used in this disclosure an “alternate signal” is acommunication and/or signal associated with an alternate flightcomponent that is transmitted from an second aircraft component of theplurality of second aircraft components to aircraft component 116. Forexample, and without limitation, second aircraft component may transmitan alternate signal comprising a propeller rotation of 520 rpms, whereinaircraft component 116, attached to flight component 108, receives thealternate signal. Aircraft component 116 may command flight component108 as a function of alternate signal. For example, and withoutlimitation, aircraft component 116 may command a rudder to rotate 3°along a vertical axis as a function of an alternate signal relating toan aileron that has raised 1.7° to exert a yaw torque on the aircraft.

Referring now to FIG. 2 , an exemplary plot of aircraft control 200(e.g. aircraft control 112 in FIG. 1 ) is shown. In particular, FIG. 2may represent the range of motion of a joystick. Aircraft control 200may include a default position 204. In some embodiments, defaultposition 204 may be referred to as the spring centered position. For thepurposes of this disclosure, the “default position” is the position thataircraft control 200 returns to or rests at when the pilot is notengaging with it. For example, a joystick usually returns to a verticalposition when the pilot is not using it. FIG. 2 also shows a maximumrange of motion 208 that aircraft control 200 is capable of As anon-limiting example, a yoke may be pushed forward to pitch down thenose of an aircraft and may be pulled back to pitch up the nose of anaircraft. Maximum range of motion 208 may represent the maximum amountthat the yoke can be “pushed forward” or “pulled back.” As anothernon-limiting example, a joystick has a fixed range of motion. Generally,a joystick may be tilted in any direction, but may be limited in thetilt that can be achieved. Thus, maximum range of motion 208, mayrepresent the maximum range of motion of a joystick.

With continued reference to FIG. 2 , aircraft control 200 may have anassociated first threshold value 212. First threshold value 212 mayrepresent a displacement from default position 204. In some embodiments,first threshold value 212 can be plotted on a linear scale. As anon-limiting example, where aircraft control 200 is a pedal, firstthreshold value 212 may be associated with the depression of the pedal.As a non-limiting embodiment, first threshold value 212 may be plottedon an X-Y plane when aircraft control 200 is a joystick. For example,the angle and tilt of the joystick may be translated into X-Ycoordinates. In some embodiments, aircraft control 200 may transmit anengagement datum to a command sensor (e.g. command sensor 120 in FIG. 1). When the displacement of aircraft control 200 is less than firstthreshold value 212, aircraft control 200 may be considered to bedisengaged. When aircraft control 200 is detected to be disengaged(i.e., the displacement of aircraft control 200 is less than firstthreshold value 212) aircraft control 200 may send an engagement datumto a command sensor (e.g. command sensor 120 in FIG. 1 ). In someembodiments, engagement datum may be a binary value to indicate thataircraft control 200 is either engaged or disengaged. As a non-limitingexample, the engagement datum may be a “0” to indicate that aircraftcontrol 200 has been detected to be disengaged. As a non-limitingexample, aircraft control 200 may be detected to be at a first point216. The displacement of first point 216 may be less than firstthreshold value 212. In response to this input, in this embodiment,aircraft control 200 may send an engagement datum to a command sensorindicating that aircraft control 200 is disengaged.

With continued reference to FIG. 2 , aircraft control 200 may have anassociated second threshold value 220. Second threshold value 220 mayrepresent a displacement from default position 204. In some embodiments,second threshold value 220 can be plotted on a linear scale. As anon-limiting example, where aircraft control 200 is a pedal, secondthreshold value 220 may be associated with the depression of the pedal.As a non-limiting embodiment, second threshold value 220 may be plottedon an X-Y plane when aircraft control 200 is a joystick. For example,the angle and tilt of the joystick may be translated into X-Ycoordinates. When the displacement of aircraft control 200 is greaterthan second threshold value 220, aircraft control 200 may be consideredto be engaged. When aircraft control 200 is detected to be engaged(i.e., the displacement of aircraft control 200 is greater than secondthreshold value 220) aircraft control 200 may send an engagement datumto a command sensor (e.g. command sensor 120 in FIG. 1 ). As anon-limiting example, the engagement datum may be a “1” to indicate thataircraft control 200 has been detected to be engaged. As a non-limitingexample, aircraft control 200 may be detected to be at a second point224. The displacement of second point 224 may be greater than secondthreshold value 220. In response to this input, in this embodiment,aircraft control 200 may send an engagement datum to a command sensorindicating that aircraft control 200 is engaged.

With continued reference to FIG. 2 , in some embodiments, secondthreshold value 220 and first threshold value 212 may be the same value.In some other embodiments, second threshold value 220 may be greaterthan first threshold value 212. When the displacement of aircraftcontrol 200 is greater than first threshold value 212 and less thansecond threshold value 220, then aircraft control 200 may send anengagement datum to a command sensor that corresponds to the lastengagement datum that was sent to the command sensor. As a non-limitingexample, aircraft control 200 may be detected to be at a third point228. Third point 228 may be at a displacement that is less than secondthreshold value 220 and more than first threshold value 212. In thiscase, the aircraft control 200 may send an engagement datum to a commandsensor that is the same as the previous engagement datum sent to thecommand sensor. As a non-limiting example, if the previous displacementof aircraft control 200 was less than first threshold value 212, and thedisplacement of aircraft control 200 is now more than first thresholdvalue 212, but less than second threshold value 220, aircraft control200 may send an engagement datum to a command sensor indicating thataircraft control 200 is disengaged. As a non-limiting example, if theprevious displacement of aircraft control 200 was greater than secondthreshold value 220, and the displacement of aircraft control 200 is nowless than second threshold value 220, but greater than first thresholdvalue 212, aircraft control 200 may send an engagement datum to acommand sensor indicating that aircraft control 200 is engaged.

Referring now to FIG. 3 , an over-head view of an exemplary flight path300 for aircraft 304 is depicted. In FIG. 3 , drift 308 is parallel tothe desired velocity 312. Drift 308 may be due to external factors, suchas a crosswind or updraft, or internal factors, such as sensor noise.Desired velocity may be any input from the pilot of aircraft 304 thataffects the position, direction, velocity, acceleration, and the like ofaircraft 304. As depicted in FIG. 3 , desired velocity 312 represents adesired velocity for aircraft 304. While desired velocity 312 mayrepresent the pilot input velocity for aircraft 304, due to factors suchas drift 308, the actual velocity of the aircraft may not match desiredvelocity 312. This is illustrated by a measured velocity 316. Measuredvelocity 316 is the actual velocity of aircraft 304 as measured byon-board sensors such as, as a non-limiting example, velocity sensor 128in FIG. 1 . A velocity supplemental attitude generator (e.g. velocitysupplemental attitude generator 620 in FIG. 6 ) may produce a velocitysupplemental attitude (VSA) (not shown). In this embodiment, drift 308is parallel to desired velocity 312. This means that the drift 308 onlyslows down or speeds up the aircraft 304. The drift, in this embodiment,would not cause the aircraft to experience any lateral drift. As theaircraft is not experiencing any lateral drift, the VSA may be zero. TheVSA may be calculated using:

${VSA} = {{K_{d}\left( {f_{p}\left( {{{{\overset{˙}{x}}_{d}(t)} - {{\overset{\hat{.}}{x}}_{d}(t)}},{{desired}{direction}}} \right)} \right)} + {K_{i}{\int{{f_{p}\left( {{{{\overset{.}{x}}_{d}(t)} - {{\overset{\hat{˙}}{x}}_{d}(t)}},{{desired}{direction}}} \right)}{dt}}}}}$

In the equation above, K_(d) is derivative gain. f_(p) is a projectionfunction that take two inputs, the first input is perpendicular to thesecond input. {dot over (x)}_(d)(t) is the desired velocity 312 as afunction of time in the form of a desired velocity. {dot over({circumflex over (x)})}_(d)(t) is the measured velocity 316 as afunction of time. desired direction is the desired direction of aircraft304; this can be obtained, as a non-limiting example, from the desiredvelocity 312. Finally, K_(i) is integral gain. In this case, since drift308 and desired velocity 312 are parallel to one another, f_(p) willoutput a zero value. Thus, VSA will be equal to zero.

Referring now to FIG. 4 , another over-head view of an exemplary flightpath 400 for aircraft 404 is depicted. In this embodiment, unlike inFIG. 3 , drift 408 is perpendicular to the direction of motion, notparallel. Additionally, in this embodiment, drift 408 is perpendicularto desired velocity 412. Desired velocity may be any input from thepilot of aircraft 404 that affects the position, direction, velocity,acceleration, and the like of aircraft 404. This results in a measuredvelocity 416 that has elements that are both parallel to desiredvelocity 412 and perpendicular to desired velocity 412. Measuredvelocity 416 is the actual velocity of aircraft 404 as measured byon-board sensors such as, as a non-limiting example, velocity sensor 128in FIG. 1 . A velocity supplemental attitude generator (e.g. velocitysupplemental attitude generator 620 in FIG. 6 ) may produce a VSA (notshown). In this embodiment, since drift 408 and desired velocity 412 areperpendicular, the aircraft 404 will experience lateral drift. As theaircraft 404., in this embodiment, will experience lateral drift, VSAwill not be equal to zero. Returning to the equation for VSA laid outabove, since drift 408 and desired velocity 412 are not parallel to oneanother, f_(p) will be non-zero. Therefore, VSA may be non-zero. In thiscase, VSA and the aircraft attitude may be combined to obtain anaggregate attitude. Aircraft attitude, for the purposes of thisdisclosure, may include roll, pitch, yaw, any aircraft orientationmeasurement, aircraft velocity, aircraft speed, aircraft acceleration,and the like. As a non-limiting example, measured velocity 416 may be acomponent of the aircraft attitude.

Referring now to FIG. 5 , an aircraft 500 is depicted. Aircraft 500 maybe hovering. For the purposes of this disclosure, “hovering” means thatan aircraft is maintaining substantially the same vertical position,while not substantially moving laterally. In FIG. 5 , aircraft 500 maybe subjected to drift 504. Drift 504, as a non-limiting example, may bedue to wind. As another non-limiting example, drift 504 may be due tosensor noise. Aircraft 500 may have a hover position 508. Hover positionis the position at which aircraft 500 is hovering. Hover position may beset by the pilot using an aircraft control. In some embodiments, drift504 may cause aircraft 500 to deviate from hover position 508. In someembodiments, if aircraft 500 drifts too far away from hover position508, aircraft may be configured to automatically land. In order tocompensate for drift 504, a position supplemental attitude (PSA) may beused in order to keep aircraft 500 at hover position 508. PSA may beobtained using:

PSA=K _(p)(x _(d)(t)−{circumflex over (x)} _(d)(t))+K _(d)({dot over(x)} _(d)(t)−{circumflex over ({dot over (x)})} _(d)(t)+K _(i)∫(x_(d)(t)−{circumflex over (x)} _(d)(t))dt

In the above equation, K_(p) is a proportional gain. x_(d)(t) is thepilot input position as a function of time. {circumflex over (x)}_(d)(t)is the actual position of the aircraft as a function of time. K_(d) is aderivative gain. {dot over (x)}_(d)(t) is the desired velocity as afunction of time. {circumflex over ({dot over (x)})}_(d)(t) is themeasured velocity as a function of time. K_(i) is an integral gain. As anon-limiting example, for the purposes of illustration, in the casewhere there is no drift, x_(d)(t)={circumflex over (x)}_(d)(t) and {dotover (x)}_(d)(t)={circumflex over ({dot over (x)})}_(d)(t). This meansthat, applying the above equation for PSA, PSA will be equal to zero.This makes sense as, in the absence of drift, a PSA is not required.

Referring now to FIG. 6 , a diagram for a distributed supplementalattitude control system 600 is depicted. System 600 includes an aircraftcontrol 604. Aircraft control 604 may include an input device such as ajoystick, pedals, inceptor stick, or the like. In some embodiments,aircraft control 604 may be a spring-centered joystick. Aircraft control604 may be consistent with some embodiments of aircraft control 112 inFIG. 1 . Aircraft control 604 outputs a signal containing the pilot'sinputs. As a non-limiting example, wherein aircraft control 604 is ajoystick, aircraft control 604 may output a signal indicating theposition of the joystick. In some embodiments, the signal from aircraftcontrol 604 may be fed through a signal shaping component. The signalshaping component may shape the signal from aircraft control 604according to a set of rules. As a non-limiting example, in someembodiments, signal shaping component may smooth out sudden changes inthe aircraft control 604 signal.

With continued reference to FIG. 6 , system 600 may include an attitudegenerator 608. Attitude generator 608 may receive a signal from aircraftcontrol 604. In some embodiments, attitude generator 608 may receive asignal from a signal shaping component. Attitude generator 608 may takethe signal that it receives and generate, as non-limiting examples, aninput roll, an input pitch, an input yaw, angular velocity, angularacceleration, velocity, acceleration, and the like.

With continued reference to FIG. 6 , system 600 includes a switch 612.Switch 612 chooses whether system 600 uses the supplemental attitudefrom the position supplemental attitude generator 616 and velocitysupplemental attitude generator 620. Switch 612 connects positionsupplemental attitude generator 616 to summation device 624 whenaircraft control 604 is detected to be disengaged. Switch 612 connectsvelocity supplemental attitude generator 620 to summation device 624when aircraft control 604 is detected to be engaged. As a non-limitingembodiment when aircraft control 604 is a joystick, for example,aircraft control 604 may be disengaged when the joystick is in itsspring-centered position. Additionally, the joystick may be consideredto be engaged when the joystick is displaced from the spring-centeredposition. In some embodiments, switch 612 may receive an engagementdatum from a command sensor 628. Engagement datum may be calculatedusing any method discussed above with reference to FIG. 2 .

With continued reference to FIG. 6 , in some embodiments, switch 612 maynot binarily switch between the velocity supplemental attitude output byvelocity supplemental attitude generator 620 and the positionsupplemental attitude output by the position supplemental attitudegenerator. In some embodiments, instead, switch 612 may blend thevelocity supplemental attitude output by velocity supplemental attitudegenerator 620 with the position supplemental attitude output by theposition supplemental attitude generator. This embodiment may be used,in particular, when the engagement datum indicates that aircraft controlhas switched from engaged to disengaged. In this case, the supplementalattitude output by switch 612 to summation device 624 may initially be100% the velocity supplemental attitude and may transition to being 100%the position supplemental attitude. As a non-limiting example, thistransition may be linear. This transition may take place over a settransition time. As a non-limiting example, the transition time may be 1second. As a non-limiting example, the transition time may be less than1 second. As a non-limiting example, the transition time may be 10seconds. As a non-limiting example, the transition time may be 5seconds. As a non-limiting example, the transition may be parabolic.Another case in which the velocity and position supplemental attitudesmay be blended is when the engagement datum indicates that aircraftcontrol has switched from disengaged to engaged. In this case, thesupplemental attitude output by switch 612 to summation device 624 mayinitially be 100% the position supplemental attitude and may transitionto being 100% the velocity supplemental attitude. As a non-limitingexample, this transition may be linear. This transition may take placeover a set transition time. As a non-limiting example, the transitiontime may be 1 second. As a non-limiting example, the transition time maybe less than 1 second. As a non-limiting example, the transition timemay be 10 seconds. As a non-limiting example, the transition time may be5 seconds. As a non-limiting example, the transition may be parabolic.

With continued reference to FIG. 6 , system 600 includes a summationdevice 624. Summation device 624 may be configured to sum the aircraftattitude received from attitude generator 608 with the supplementalattitude received from switch 612. Depending on the state of switch 612,the supplemental attitude received from switch 612 may be a positionsupplemental attitude from position supplemental attitude generator 616or it may be a velocity supplemental attitude from velocity supplementalattitude generator 620. Summation device 624 outputs an aggregateattitude to command sensor 628.

With continued reference to FIG. 6 , aircraft component 632 may beconsistent with any aircraft component disclosed as part of thisdisclosure. In particular, aircraft component 632 may be consistent withaircraft component 116 in FIG. 1 . Aircraft component 632 receives theaggregate attitude from command sensor 628. Aircraft component 632 mayoutput a command to flight component 636. Flight component 636 may beconsistent with any flight component disclosed as part of thisdisclosure. In particular, flight component 636 may be consistent withflight component 108 in FIG. 1 . The command may cause the aircraft tochange states. As non-limiting examples, the aircraft's position, roll,pitch, yaw, velocity, acceleration . . . etc. may change. This statechange may be detected by component sensor 640. Component sensor 640 maybe any suitable sensor, such as a GPS, radar, lidar, accelerometer,gyroscope, compass, etc. Additionally, component sensor 640 may be anarray of different sensors; the array may include different types ofsensors. Component sensor 640 may be consistent with any sensordisclosed as part of this disclosure that would be suitable to detect achange in aircraft state.

With continued reference to FIG. 6 , the attitude data detected bycomponent sensor 640 may be fed back into aircraft component 632 as partof a feedback loop. This may allow aircraft component 632 to makeadjustments to its commands. Velocity supplemental attitude generator620 receives the velocity data detected by component sensor 640.Position supplemental attitude generator 616 receives both the positionand velocity data detected by component sensor 640.

With continued reference to FIG. 6 , velocity supplemental attitudegenerator 620 and position supplemental attitude generator 616 may becomputing devices, such as computer system 1100 in FIG. 11 or flightcontroller 904 in FIG. 9 . Velocity supplemental attitude generator 620may carry out the processes described in FIGS. 3 and 4 and theparagraphs pertaining to FIGS. 3 and 4 . Position supplemental attitudegenerator 616 may carry out the processes described in FIG. 5 and theparagraphs pertaining to FIG. 5 .

Now referring to FIG. 7 , an exemplary embodiment of aircraft 104 isillustrated. In an embodiment, and without limitation, aircraft 104 mayinclude a fuselage 700. As used in this disclosure a “fuselage” is themain body of an aircraft, or in other words, the entirety of theaircraft except for the cockpit, nose, wings, empennage, nacelles, anyand all control surfaces, and generally contains an aircraft's payload.Fuselage 700 may comprise structural elements that physically supportthe shape and structure of an aircraft. Structural elements may take aplurality of forms, alone or in combination with other types. Structuralelements may vary depending on the construction type of aircraft andspecifically, the fuselage. Fuselage 700 may comprise a truss structure.A truss structure is often used with a lightweight aircraft andcomprises welded steel tube trusses. A truss, as used herein, is anassembly of beams that create a rigid structure, often in combinationsof triangles to create three-dimensional shapes. A truss structure mayalternatively comprise wood construction in place of steel tubes, or acombination thereof. In embodiments, structural elements may comprisesteel tubes and/or wood beams. In an embodiment, and without limitation,structural elements may include an aircraft skin. Aircraft skin may belayered over the body shape constructed by trusses. Aircraft skin maycomprise a plurality of materials such as plywood sheets, aluminum,fiberglass, and/or carbon fiber, the latter of which will be addressedin greater detail later in this paper.

Still referring to FIG. 7 , fuselage 700 may comprise geodesicconstruction. Geodesic structural elements may include stringers woundabout formers (which may be alternatively called station frames) inopposing spiral directions. A stringer, as used herein, is a generalstructural element that comprises a long, thin, and rigid strip of metalor wood that is mechanically coupled to and spans the distance from,station frame to station frame to create an internal skeleton on whichto mechanically couple aircraft skin. A former (or station frame) caninclude a rigid structural element that is disposed along the length ofthe interior of fuselage 700 orthogonal to the longitudinal (nose totail) axis of the aircraft and forms the general shape of fuselage 700.A former may comprise differing cross-sectional shapes at differinglocations along fuselage 700, as the former is the structural elementthat informs the overall shape of a fuselage 700 curvature. Inembodiments, aircraft skin can be anchored to formers and strings suchthat the outer mold line of the volume encapsulated by the formers andstringers comprises the same shape as aircraft 104 when installed. Inother words, former(s) may form a fuselage's ribs, and the stringers mayform the interstitials between such ribs. The spiral orientation ofstringers about formers provides uniform robustness at any point on anaircraft fuselage such that if a portion sustains damage, anotherportion may remain largely unaffected. Aircraft skin would bemechanically coupled to underlying stringers and formers and mayinteract with a fluid, such as air, to generate lift and performmaneuvers.

In an embodiment, and still referring to FIG. 7 , fuselage 700 maycomprise monocoque construction. Monocoque construction may include aprimary structure that forms a shell (or skin in an aircraft's case) andsupports physical loads. Monocoque fuselages are fuselages in which theaircraft skin or shell is also the primary structure. In monocoqueconstruction aircraft skin would support tensile and compressive loadswithin itself and true monocoque aircraft can be further characterizedby the absence of internal structural elements. Aircraft skin in thisconstruction method is rigid and can sustain its shape with nostructural assistance form underlying skeleton-like elements. Monocoquefuselage may comprise aircraft skin made from plywood layered in varyinggrain directions, epoxy-impregnated fiberglass, carbon fiber, or anycombination thereof.

Still referring to FIG. 7 , fuselage 700 can include a semi-monocoqueconstruction. Semi-monocoque construction, as used herein, is a partialmonocoque construction, wherein a monocoque construction is describeabove detail. In semi-monocoque construction, fuselage 700 may derivesome structural support from stressed aircraft skin and some structuralsupport from underlying frame structure made of structural elements.Formers or station frames can be seen running transverse to the longaxis of fuselage 700 with circular cutouts which are generally used inreal-world manufacturing for weight savings and for the routing ofelectrical harnesses and other modern on-board systems. In asemi-monocoque construction, stringers are the thin, long strips ofmaterial that run parallel to fuselage's long axis. Stringers may bemechanically coupled to formers permanently, such as with rivets.Aircraft skin may be mechanically coupled to stringers and formerspermanently, such as by rivets as well. A person of ordinary skill inthe art will appreciate that there are numerous methods for mechanicalfastening of the aforementioned components like crews, nails, dowels,pins, anchors, adhesives like glue or epoxy, or bolts and nuts, to namea few. A subset of fuselage under the umbrella of semi-monocoqueconstruction is unibody vehicles. Unibody, which is short for “unitizedbody” or alternatively “unitary construction”, vehicles arecharacterized by a construction in which the body, floor plan, andchassis form a single structure. In the aircraft world, unibody wouldcomprise the internal structural elements like formers and stringers areconstructed in one piece, integral to the aircraft skin as well as anyfloor construction like a deck.

Still referring to FIG. 7 , stringers and formers which account for thebulk of any aircraft structure excluding monocoque construction can bearranged in a plurality of orientations depending on aircraft operationand materials. Stringers may be arranged to carry axial (tensile orcompressive), shear, bending or torsion forces throughout their overallstructure. Due to their coupling to aircraft skin, aerodynamic forcesexerted on aircraft skin will be transferred to stringers. The locationof said stringers greatly informs the type of forces and loads appliedto each and every stringer, all of which may be handled by materialselection, cross-sectional area, and mechanical coupling methods of eachmember. The same assessment may be made for formers. In general, formersare significantly larger in cross-sectional area and thickness,depending on location, than stringers. Both stringers and formers maycomprise aluminum, aluminum alloys, graphite epoxy composite, steelalloys, titanium, or an undisclosed material alone or in combination.

In an embodiment, and still referring to FIG. 7 , stressed skin, whenused in semi-monocoque construction is the concept where the skin of anaircraft bears partial, yet significant, load in the overall structuralhierarchy. In other words, the internal structure, whether it be a frameof welded tubes, formers and stringers, or some combination, is notsufficiently strong enough by design to bear all loads. The concept ofstressed skin is applied in monocoque and semi-monocoque constructionmethods of fuselage 700. Monocoque comprises only structural skin, andin that sense, aircraft skin undergoes stress by applied aerodynamicfluids imparted by the fluid. Stress as used in continuum mechanics canbe described in pound-force per square inch (lbf/in²) or Pascals (Pa).In semi-monocoque construction stressed skin bears part of theaerodynamic loads and additionally imparts force on the underlyingstructure of stringers and formers.

Still referring to FIG. 7 , aircraft 104 may include a plurality oflaterally extending elements 704 attached to fuselage 700. As used inthis disclosure a “laterally extending element” is an element thatprojects essentially horizontally from fuselage, including an outrigger,a spar, and/or a fixed wing that extends from fuselage 700. Wings may bestructures which include airfoils configured to create a pressuredifferential resulting in lift. Wings may generally dispose on the leftand right sides of the aircraft symmetrically, at a point between noseand empennage. Wings may comprise a plurality of geometries in planformview, swept swing, tapered, variable wing, triangular, oblong,elliptical, square, among others. A wing's cross section geometry maycomprise an airfoil. An “airfoil” as used in this disclosure is a shapespecifically designed such that a fluid flowing above and below it exertdiffering levels of pressure against the top and bottom surface. Inembodiments, the bottom surface of an aircraft can be configured togenerate a greater pressure than does the top, resulting in lift.Laterally extending element 704 may comprise differing and/or similarcross-sectional geometries over its cord length or the length from wingtip to where wing meets the aircraft's body. One or more wings may besymmetrical about the aircraft's longitudinal plane, which comprises thelongitudinal or roll axis reaching down the center of the aircraftthrough the nose and empennage, and the plane's yaw axis. Laterallyextending element 704 may comprise controls surfaces configured to becommanded by a pilot or pilots to change a wing's geometry and thereforeits interaction with a fluid medium, like air. Control surfaces maycomprise flaps, ailerons, tabs, spoilers, and slats, among others. Thecontrol surfaces may dispose on the wings in a plurality of locationsand arrangements and in embodiments may be disposed at the leading andtrailing edges of the wings, and may be configured to deflect up, down,forward, aft, or a combination thereof. An aircraft, including adual-mode aircraft may comprise a combination of control surfaces toperform maneuvers while flying or on ground.

Still referring to FIG. 7 , aircraft 104 may include at least apropulsor 708. As used in this disclosure a “propulsor” is a componentand/or device used to propel a craft by exerting force on a fluidmedium, which may include a gaseous medium such as air or a liquidmedium such as water. In an embodiment, when a propulsor twists andpulls air behind it, it will, at the same time, push an aircraft forwardwith an equal amount of force and/or thrust. The more air pulled behindan aircraft, the greater the thrust with which the aircraft is pushedforward. Propulsor 708 may include any device or component that consumeselectrical power on demand to propel an electric aircraft in a directionor other vehicle while on ground or in-flight. In an embodiment,propulsor 708 may include a puller component. As used in this disclosurea “puller component” is a component that pulls and/or tows an aircraftthrough a medium. As a non-limiting example, puller component mayinclude a flight component 712 such as a puller propeller, a pullermotor, a puller propulsor, and the like. Additionally, or alternatively,puller component may include a plurality of puller flight components. Inanother embodiment, aircraft 104 may include a pusher component 716. Asused in this disclosure a “pusher component” is a component that pushesand/or thrusts an aircraft through a medium. As a non-limiting example,pusher component 716 may include a pusher component such as a pusherpropeller, a pusher motor, a pusher propulsor, and the like.Additionally, or alternatively, pusher component 716 may include aplurality of pusher components.

Referring now to FIG. 8 , a flow chart of an embodiment of a method ofdistributed control with supplemental attitude adjustment 800 is shown.Method 800 includes a step 805 of receiving aircraft data. Step 805includes a step of receiving, from a command sensor attached to anaircraft control, an aircraft command. Command sensor may be consistentwith any command sensor disclosed in this disclosure. Aircraft controlmay be consistent with any aircraft control disclosed in thisdisclosure. Aircraft command is a command that instructs a flightcomponent to perform an action or motion, such as, as non-limitingexamples, increasing thrust or changing the angle of a control surface.Aircraft command may be consistent with any aircraft command disclosedas part of this disclosure.

With continued reference to FIG. 8 , method 800 further includes a step810 of generating a supplemental attitude. Step 810 includes a step ofgenerating a response command directing the flight components as afunction of a supplemental attitude. Response command may be consistentwith any response command discloses as part of this disclosure. Thisstep includes generating a supplemental attitude as a function of anengagement datum. Engagement datum may be consistent with any engagementdatum disclosed in this disclosure. Generating a supplemental attitudeincluding, choosing a position supplemental attitude if the engagementdatum indicates that the aircraft control is disengaged and choosing avelocity supplemental attitude if the engagement datum indicates thatthe aircraft control is engaged. The portion of this step concerningchoosing the position supplemental attitude and choosing the velocitysupplemental attitude may be implemented, for example, using switch 612in FIG. 6 . Position supplemental attitude may be consistent with anyposition supplemental attitude disclosed in this disclosure. Velocitysupplemental attitude may be consistent with any velocity supplementalattitude disclosed as part of this disclosure. Additionally, step 810includes a step of calculating an aggregate attitude, whereincalculating the aggregate attitude comprises combining the aircraftattitude with the supplemental attitude to obtain an aggregate attitude.The supplemental attitude can be either, position supplemental attitudeor velocity supplemental attitude, depending on which has been chosen asdescribed above. Aggregate attitude may be consistent with any aggregateattitude disclosed as part of this disclosure. Step 810 furthermoreincludes a step of generating the response command as a function of anaggregate attitude.

With continued reference to FIG. 8 , method 800 may include an optionalstep 815 of commanding a flight component of a plurality of flightcomponents to produce a response command based on the aggregateattitude, wherein the flight component of the plurality of flightcomponents is attached to an aircraft component of a plurality ofaircraft components. The flight component may be, as non-limitingexamples, a motor, an engine, a rotor, a control surface, and the like.The flight component may be consistent with any flight componentdisclosed as part of this disclosure

With continued reference to FIG. 8 , step 805 may further include a stepof receiving a desired velocity, the desired velocity including adesired direction of movement. Desired velocity may be consistent withany desired velocity disclosed in this disclosure. The desired directionof movement may be a component of the desired velocity. step 805 mayfurther include a step of receiving an actual velocity from a velocitysensor. Actual velocity may be consistent with any actual velocitydisclosed as part of this disclosure. Velocity sensor may be consistentwith any velocity sensor disclosed as part of this disclosure. Step 810may further include a step of generating a velocity supplementalattitude. Velocity supplemental attitude may be consistent with anyvelocity supplemental attitude disclosed in this disclosure. This stepmay be carried out by, as a non-limiting example, velocity supplementalattitude generator 620 in FIG. 6 . The step of generating a velocitysupplemental attitude may further include a step of calculating adifference between the desired velocity and the actual velocity.Additionally, the step of generating a velocity supplemental attitudemay further include a step of calculating the part of the differencethat is perpendicular to the desired direction of movement.

With continued reference to FIG. 8 , method 800 may further include astep of generating the engagement datum. The step of generating theengagement datum may include a step of calculating the displacement ofthe aircraft control from a spring-centered position. The defaultposition may be consistent with any default position disclosed in thisdisclosure. The step of generating the engagement datum also may includea step of comparing the displacement of the aircraft control against afirst threshold. First threshold may be consistent with any firstthreshold disclosed in this disclosure. The step of generating theengagement datum also may include a step of transmitting an engagementdatum to the command sensor indicating that the aircraft control isengaged if the displacement of the aircraft control exceeds the firstthreshold. The engagement datum may, as a non-limiting example, be abinary value. For example, if aircraft control is disengaged, engagementdatum may be “0.” If aircraft control is engaged, engagement datum maybe “1.”

With continued reference to FIG. 8 , the step of generating theengagement datum may further include a step of comparing thedisplacement of the aircraft control against a second threshold, whereinthe second threshold is less than the first threshold. Second thresholdmay be consistent with any second threshold disclosed in the disclosure.Additionally, the step of generating the engagement datum may furtherinclude a step of transmitting an engagement datum to the command sensorindicating that the aircraft control is disengaged if the displacementof the aircraft control does not exceed the second threshold. The firstthreshold and second threshold, in some embodiments, may be consistentwith the first threshold and second threshold, respectively, depicted inFIG. 2 . In some embodiments of method 800, aircraft control may be ajoystick. Joystick may be consistent with any joystick described as partof this disclosure.

With continued reference to FIG. 8 , step 810 may further include, aspart of generating the supplemental attitude, a step of transitioningfrom choosing a position supplemental attitude to choosing a velocitysupplemental attitude when the engagement datum indicates that theaircraft control has switched from disengaged to engaged. As anon-limiting example, the engagement datum may indicate that theaircraft control has switched from disengaged to engaged by switchingfrom “0” to “1.” In some embodiments, step 810 may further include astep of transitioning from choosing a velocity supplemental attitude tochoosing a position supplemental attitude when the engagement datumindicates that the aircraft control has switched from engaged todisengaged. As a non-limiting example, the engagement datum may indicatethat the aircraft control has switched from engaged to disengaged byswitching from “1” to “0.”

With continued reference to FIG. 8 , step 815may further include a stepof receiving an alternate signal from an second aircraft component ofthe at least an aircraft component. Alternate signal may be consistentwith any alternate signal disclosed as part of this disclosure. Secondaircraft component may be consistent with any second aircraft componentdisclosed as part of this disclosure. Step 815 may also further includea step of commanding the flight component of the plurality of flightcomponents as a function of the alternate signal. In some embodiments,step 815 may further include a step of transmitting an outgoing signalto the second aircraft component, wherein the outgoing signal containsthe aggregate attitude. In some embodiments, method 800 may furtherinclude a step of converting the aircraft command to a digitalelectronic signal. Digital electronic signal may be consistent with anydigital electronic signal disclosed as part of this disclosure.

Now referring to FIG. 9 , an exemplary embodiment 900 of a flightcontroller 904 is illustrated. As used in this disclosure a “flightcontroller” is a computing device of a plurality of computing devicesdedicated to data storage, security, distribution of traffic for loadbalancing, and flight instruction. Flight controller 904 may includeand/or communicate with any computing device as described in thisdisclosure, including without limitation a microcontroller,microprocessor, digital signal processor (DSP) and/or system on a chip(SoC) as described in this disclosure. Further, flight controller 904may include a single computing device operating independently, or mayinclude two or more computing device operating in concert, in parallel,sequentially or the like; two or more computing devices may be includedtogether in a single computing device or in two or more computingdevices. In embodiments, flight controller 904 may be installed in anaircraft, may control the aircraft remotely, and/or may include anelement installed in the aircraft and a remote element in communicationtherewith.

In an embodiment, and still referring to FIG. 9 , flight controller 904may include a signal transformation component 908. As used in thisdisclosure a “signal transformation component” is a component thattransforms and/or converts a first signal to a second signal, wherein asignal may include one or more digital and/or analog signals. Forexample, and without limitation, signal transformation component 908 maybe configured to perform one or more operations such as preprocessing,lexical analysis, parsing, semantic analysis, and the like thereof. Inan embodiment, and without limitation, signal transformation component908 may include one or more analog-to-digital convertors that transforma first signal of an analog signal to a second signal of a digitalsignal. For example, and without limitation, an analog-to-digitalconverter may convert an analog input signal to a 10-bit binary digitalrepresentation of that signal. In another embodiment, signaltransformation component 908 may include transforming one or morelow-level languages such as, but not limited to, machine languagesand/or assembly languages. For example, and without limitation, signaltransformation component 908 may include transforming a binary languagesignal to an assembly language signal. In an embodiment, and withoutlimitation, signal transformation component 908 may include transformingone or more high-level languages and/or formal languages such as but notlimited to alphabets, strings, and/or languages. For example, andwithout limitation, high-level languages may include one or more systemlanguages, scripting languages, domain-specific languages, visuallanguages, esoteric languages, and the like thereof. As a furthernon-limiting example, high-level languages may include one or morealgebraic formula languages, business data languages, string and listlanguages, object-oriented languages, and the like thereof.

Still referring to FIG. 9 , signal transformation component 908 may beconfigured to optimize an intermediate representation 912. As used inthis disclosure an “intermediate representation” is a data structureand/or code that represents the input signal. Signal transformationcomponent 908 may optimize intermediate representation as a function ofa data-flow analysis, dependence analysis, alias analysis, pointeranalysis, escape analysis, and the like thereof. In an embodiment, andwithout limitation, signal transformation component 908 may optimizeintermediate representation 912 as a function of one or more inlineexpansions, dead code eliminations, constant propagation, looptransformations, and/or automatic parallelization functions. In anotherembodiment, signal transformation component 908 may optimizeintermediate representation as a function of a machine dependentoptimization such as a peephole optimization, wherein a peepholeoptimization may rewrite short sequences of code into more efficientsequences of code. Signal transformation component 908 may optimizeintermediate representation to generate an output language, wherein an“output language,” as used herein, is the native machine language offlight controller 904. For example, and without limitation, nativemachine language may include one or more binary and/or numericallanguages.

In an embodiment, and without limitation, signal transformationcomponent 908 may include transform one or more inputs and outputs as afunction of an error correction code. An error correction code, alsoknown as error correcting code (ECC), is an encoding of a message or lotof data using redundant information, permitting recovery of corrupteddata. An ECC may include a block code, in which information is encodedon fixed-size packets and/or blocks of data elements such as symbols ofpredetermined size, bits, or the like. Reed-Solomon coding, in whichmessage symbols within a symbol set having q symbols are encoded ascoefficients of a polynomial of degree less than or equal to a naturalnumber k, over a finite field F with q elements; strings so encoded havea minimum hamming distance of k+1, and permit correction of (q−k−1)/2erroneous symbols. Block code may alternatively or additionally beimplemented using Golay coding, also known as binary Golay coding,Bose-Chaudhuri, Hocquenghuem (BCH) coding, multidimensional parity-checkcoding, and/or Hamming codes. An ECC may alternatively or additionallybe based on a convolutional code.

In an embodiment, and still referring to FIG. 9 , flight controller 904may include a reconfigurable hardware platform 916. A “reconfigurablehardware platform,” as used herein, is a component and/or unit ofhardware that may be reprogrammed, such that, for instance, a data pathbetween elements such as logic gates or other digital circuit elementsmay be modified to change an algorithm, state, logical sequence, or thelike of the component and/or unit. This may be accomplished with suchflexible high-speed computing fabrics as field-programmable gate arrays(FPGAs), which may include a grid of interconnected logic gates,connections between which may be severed and/or restored to program inmodified logic. Reconfigurable hardware platform 916 may be reconfiguredto enact any algorithm and/or algorithm selection process received fromanother computing device and/or created using machine-learningprocesses.

Still referring to FIG. 9 , reconfigurable hardware platform 916 mayinclude a logic component 920. As used in this disclosure a “logiccomponent” is a component that executes instructions on output language.For example, and without limitation, logic component may perform basicarithmetic, logic, controlling, input/output operations, and the likethereof. Logic component 920 may include any suitable processor, such aswithout limitation a component incorporating logical circuitry forperforming arithmetic and logical operations, such as an arithmetic andlogic unit (ALU), which may be regulated with a state machine anddirected by operational inputs from memory and/or sensors; logiccomponent 920 may be organized according to Von Neumann and/or Harvardarchitecture as a non-limiting example. Logic component 920 may include,incorporate, and/or be incorporated in, without limitation, amicrocontroller, microprocessor, digital signal processor (DSP), FieldProgrammable Gate Array (FPGA), Complex Programmable Logic Device(CPLD), Graphical Processing Unit (GPU), general purpose GPU, TensorProcessing Unit (TPU), analog or mixed signal processor, TrustedPlatform Module (TPM), a floating point unit (FPU), and/or system on achip (SoC). In an embodiment, logic component 920 may include one ormore integrated circuit microprocessors, which may contain one or morecentral processing units, central processors, and/or main processors, ona single metal-oxide-semiconductor chip. Logic component 920 may beconfigured to execute a sequence of stored instructions to be performedon the output language and/or intermediate representation 912. Logiccomponent 920 may be configured to fetch and/or retrieve the instructionfrom a memory cache, wherein a “memory cache,” as used in thisdisclosure, is a stored instruction set on flight controller 904. Logiccomponent 920 may be configured to decode the instruction retrieved fromthe memory cache to opcodes and/or operands. Logic component 920 may beconfigured to execute the instruction on intermediate representation 912and/or output language. For example, and without limitation, logiccomponent 920 may be configured to execute an addition operation onintermediate representation 912 and/or output language.

In an embodiment, and without limitation, logic component 920 may beconfigured to calculate a flight element 924. As used in this disclosurea “flight element” is an element of datum denoting a relative status ofaircraft. For example, and without limitation, flight element 924 maydenote one or more torques, thrusts, airspeed velocities, forces,altitudes, groundspeed velocities, directions during flight, directionsfacing, forces, orientations, and the like thereof. For example, andwithout limitation, flight element 924 may denote that aircraft iscruising at an altitude and/or with a sufficient magnitude of forwardthrust. As a further non-limiting example, flight status may denote thatis building thrust and/or groundspeed velocity in preparation for atakeoff. As a further non-limiting example, flight element 924 maydenote that aircraft is following a flight path accurately and/orsufficiently.

Still referring to FIG. 9 , flight controller 904 may include a chipsetcomponent 928. As used in this disclosure a “chipset component” is acomponent that manages data flow. In an embodiment, and withoutlimitation, chipset component 928 may include a northbridge data flowpath, wherein the northbridge dataflow path may manage data flow fromlogic component 920 to a high-speed device and/or component, such as aRAM, graphics controller, and the like thereof. In another embodiment,and without limitation, chipset component 928 may include a southbridgedata flow path, wherein the southbridge dataflow path may manage dataflow from logic component 920 to lower-speed peripheral buses, such as aperipheral component interconnect (PCI), industry standard architecture(ICA), and the like thereof. In an embodiment, and without limitation,southbridge data flow path may include managing data flow betweenperipheral connections such as ethernet, USB, audio devices, and thelike thereof. Additionally or alternatively, chipset component 928 maymanage data flow between logic component 920, memory cache, and a flightcomponent 932. As used in this disclosure a “flight component” is aportion of an aircraft that can be moved or adjusted to affect one ormore flight elements. For example, flight component932 may include acomponent used to affect the aircrafts' roll and pitch which maycomprise one or more ailerons. As a further example, flight component932 may include a rudder to control yaw of an aircraft. In anembodiment, chipset component 928 may be configured to communicate witha plurality of flight components as a function of flight element 924.For example, and without limitation, chipset component 928 may transmitto an aircraft rotor to reduce torque of a first lift propulsor andincrease the forward thrust produced by a pusher component to perform aflight maneuver.

In an embodiment, and still referring to FIG. 9 , flight controller 904may be configured generate an autonomous function. As used in thisdisclosure an “autonomous function” is a mode and/or function of flightcontroller 904 that controls aircraft automatically. For example, andwithout limitation, autonomous function may perform one or more aircraftmaneuvers, take offs, landings, altitude adjustments, flight levelingadjustments, turns, climbs, and/or descents. As a further non-limitingexample, autonomous function may adjust one or more airspeed velocities,thrusts, torques, and/or groundspeed velocities. As a furthernon-limiting example, autonomous function may perform one or more flightpath corrections and/or flight path modifications as a function offlight element 924. In an embodiment, autonomous function may includeone or more modes of autonomy such as, but not limited to, autonomousmode, semi-autonomous mode, and/or non-autonomous mode. As used in thisdisclosure “autonomous mode” is a mode that automatically adjusts and/orcontrols aircraft and/or the maneuvers of aircraft in its entirety. Forexample, autonomous mode may denote that flight controller 904 willadjust the aircraft. As used in this disclosure a “semi-autonomous mode”is a mode that automatically adjusts and/or controls a portion and/orsection of aircraft. For example, and without limitation,semi-autonomous mode may denote that a pilot will control thepropulsors, wherein flight controller 904 will control the aileronsand/or rudders. As used in this disclosure “non-autonomous mode” is amode that denotes a pilot will control aircraft and/or maneuvers ofaircraft in its entirety.

In an embodiment, and still referring to FIG. 9 , flight controller 904may generate autonomous function as a function of an autonomousmachine-learning model. As used in this disclosure an “autonomousmachine-learning model” is a machine-learning model to produce anautonomous function output given flight element 924 and a pilot signal936 as inputs; this is in contrast to a non-machine learning softwareprogram where the commands to be executed are determined in advance by auser and written in a programming language. As used in this disclosure a“pilot signal” is an element of datum representing one or more functionsa pilot is controlling and/or adjusting. For example, pilot signal 936may denote that a pilot is controlling and/or maneuvering ailerons,wherein the pilot is not in control of the rudders and/or propulsors. Inan embodiment, pilot signal 936 may include an implicit signal and/or anexplicit signal. For example, and without limitation, pilot signal 936may include an explicit signal, wherein the pilot explicitly statesthere is a lack of control and/or desire for autonomous function. As afurther non-limiting example, pilot signal 936 may include an explicitsignal directing flight controller 904 to control and/or maintain aportion of aircraft, a portion of the flight plan, the entire aircraft,and/or the entire flight plan. As a further non-limiting example, pilotsignal 936 may include an implicit signal, wherein flight controller 904detects a lack of control such as by a malfunction, torque alteration,flight path deviation, and the like thereof. In an embodiment, andwithout limitation, pilot signal 936 may include one or more explicitsignals to reduce torque, and/or one or more implicit signals thattorque may be reduced due to reduction of airspeed velocity. In anembodiment, and without limitation, pilot signal 936 may include one ormore local and/or global signals. For example, and without limitation,pilot signal 936 may include a local signal that is transmitted by apilot and/or crew member. As a further non-limiting example, pilotsignal 936 may include a global signal that is transmitted by airtraffic control and/or one or more remote users that are incommunication with the pilot of aircraft. In an embodiment, pilot signal936 may be received as a function of a tri-state bus and/or multiplexorthat denotes an explicit pilot signal should be transmitted prior to anyimplicit or global pilot signal.

Still referring to FIG. 9 , autonomous machine-learning model mayinclude one or more autonomous machine-learning processes such assupervised, unsupervised, or reinforcement machine-learning processesthat flight controller 904 and/or a remote device may or may not use inthe generation of autonomous function. As used in this disclosure“remote device” is an external device to flight controller 904.Additionally or alternatively, autonomous machine-learning model mayinclude one or more autonomous machine-learning processes that afield-programmable gate array (FPGA) may or may not use in thegeneration of autonomous function. Autonomous machine-learning processmay include, without limitation machine learning processes such assimple linear regression, multiple linear regression, polynomialregression, support vector regression, ridge regression, lassoregression, elasticnet regression, decision tree regression, randomforest regression, logistic regression, logistic classification,K-nearest neighbors, support vector machines, kernel support vectormachines, naive bayes, decision tree classification, random forestclassification, K-means clustering, hierarchical clustering,dimensionality reduction, principal component analysis, lineardiscriminant analysis, kernel principal component analysis, Q-learning,State Action Reward State Action (SARSA), Deep-Q network, Markovdecision processes, Deep Deterministic Policy Gradient (DDPG), or thelike thereof.

In an embodiment, and still referring to FIG. 9 , autonomous machinelearning model may be trained as a function of autonomous training data,wherein autonomous training data may correlate a flight element, pilotsignal, and/or simulation data to an autonomous function. For example,and without limitation, a flight element of an airspeed velocity, apilot signal of limited and/or no control of propulsors, and asimulation data of required airspeed velocity to reach the destinationmay result in an autonomous function that includes a semi-autonomousmode to increase thrust of the propulsors. Autonomous training data maybe received as a function of user-entered valuations of flight elements,pilot signals, simulation data, and/or autonomous functions. Flightcontroller 904 may receive autonomous training data by receivingcorrelations of flight element, pilot signal, and/or simulation data toan autonomous function that were previously received and/or determinedduring a previous iteration of generation of autonomous function.Autonomous training data may be received by one or more remote devicesand/or FPGAs that at least correlate a flight element, pilot signal,and/or simulation data to an autonomous function. Autonomous trainingdata may be received in the form of one or more user-enteredcorrelations of a flight element, pilot signal, and/or simulation datato an autonomous function.

Still referring to FIG. 9 , flight controller 904 may receive autonomousmachine-learning model from a remote device and/or FPGA that utilizesone or more autonomous machine learning processes, wherein a remotedevice and an FPGA is described above in detail. For example, andwithout limitation, a remote device may include a computing device,external device, processor, FPGA, microprocessor and the like thereof.Remote device and/or FPGA may perform the autonomous machine-learningprocess using autonomous training data to generate autonomous functionand transmit the output to flight controller 904. Remote device and/orFPGA may transmit a signal, bit, datum, or parameter to flightcontroller 904 that at least relates to autonomous function.Additionally or alternatively, the remote device and/or FPGA may providean updated machine-learning model. For example, and without limitation,an updated machine-learning model may be comprised of a firmware update,a software update, an autonomous machine-learning process correction,and the like thereof. As a non-limiting example a software update mayincorporate a new simulation data that relates to a modified flightelement. Additionally or alternatively, the updated machine learningmodel may be transmitted to the remote device and/or FPGA, wherein theremote device and/or FPGA may replace the autonomous machine-learningmodel with the updated machine-learning model and generate theautonomous function as a function of the flight element, pilot signal,and/or simulation data using the updated machine-learning model. Theupdated machine-learning model may be transmitted by the remote deviceand/or FPGA and received by flight controller 904 as a software update,firmware update, or corrected autonomous machine-learning model. Forexample, and without limitation autonomous machine learning model mayutilize a neural net machine-learning process, wherein the updatedmachine-learning model may incorporate a gradient boostingmachine-learning process.

Still referring to FIG. 9 , flight controller 904 may include, beincluded in, and/or communicate with a mobile device such as a mobiletelephone or smartphone. Further, flight controller may communicate withone or more additional devices as described below in further detail viaa network interface device. The network interface device may be utilizedfor commutatively connecting a flight controller to one or more of avariety of networks, and one or more devices. Examples of a networkinterface device include, but are not limited to, a network interfacecard (e.g., a mobile network interface card, a LAN card), a modem, andany combination thereof. Examples of a network include, but are notlimited to, a wide area network (e.g., the Internet, an enterprisenetwork), a local area network (e.g., a network associated with anoffice, a building, a campus or other relatively small geographicspace), a telephone network, a data network associated with atelephone/voice provider (e.g., a mobile communications provider dataand/or voice network), a direct connection between two computingdevices, and any combinations thereof. The network may include anynetwork topology and can may employ a wired and/or a wireless mode ofcommunication.

In an embodiment, and still referring to FIG. 9 , flight controller 904may include, but is not limited to, for example, a cluster of flightcontrollers in a first location and a second flight controller orcluster of flight controllers in a second location. Flight controller904 may include one or more flight controllers dedicated to datastorage, security, distribution of traffic for load balancing, and thelike. Flight controller 904 may be configured to distribute one or morecomputing tasks as described below across a plurality of flightcontrollers, which may operate in parallel, in series, redundantly, orin any other manner used for distribution of tasks or memory betweencomputing devices. For example, and without limitation, flightcontroller 904 may implement a control algorithm to distribute and/orcommand the plurality of flight controllers. As used in this disclosurea “control algorithm” is a finite sequence of well-defined computerimplementable instructions that may determine the flight component ofthe plurality of flight components to be adjusted. For example, andwithout limitation, control algorithm may include one or more algorithmsthat reduce and/or prevent aviation asymmetry. As a further non-limitingexample, control algorithms may include one or more models generated asa function of a software including, but not limited to Simulink byMathWorks, Natick, Massachusetts, USA. In an embodiment, and withoutlimitation, control algorithm may be configured to generate anauto-code, wherein an “auto-code,” is used herein, is a code and/oralgorithm that is generated as a function of the one or more modelsand/or software's. In another embodiment, control algorithm may beconfigured to produce a segmented control algorithm. As used in thisdisclosure a “segmented control algorithm” is control algorithm that hasbeen separated and/or parsed into discrete sections. For example, andwithout limitation, segmented control algorithm may parse controlalgorithm into two or more segments, wherein each segment of controlalgorithm may be performed by one or more flight controllers operatingon distinct flight components.

In an embodiment, and still referring to FIG. 9 , control algorithm maybe configured to determine a segmentation boundary as a function ofsegmented control algorithm. As used in this disclosure a “segmentationboundary” is a limit and/or delineation associated with the segments ofthe segmented control algorithm. For example, and without limitation,segmentation boundary may denote that a segment in the control algorithmhas a first starting section and/or a first ending section. As a furthernon-limiting example, segmentation boundary may include one or moreboundaries associated with an ability of flight component 932. In anembodiment, control algorithm may be configured to create an optimizedsignal communication as a function of segmentation boundary. Forexample, and without limitation, optimized signal communication mayinclude identifying the discrete timing required to transmit and/orreceive the one or more segmentation boundaries. In an embodiment, andwithout limitation, creating optimized signal communication furthercomprises separating a plurality of signal codes across the plurality offlight controllers. For example, and without limitation the plurality offlight controllers may include one or more formal networks, whereinformal networks transmit data along an authority chain and/or arelimited to task-related communications. As a further non-limitingexample, communication network may include informal networks, whereininformal networks transmit data in any direction. In an embodiment, andwithout limitation, the plurality of flight controllers may include achain path, wherein a “chain path,” as used herein, is a linearcommunication path comprising a hierarchy that data may flow through. Inan embodiment, and without limitation, the plurality of flightcontrollers may include an all-channel path, wherein an “all-channelpath,” as used herein, is a communication path that is not restricted toa particular direction. For example, and without limitation, data may betransmitted upward, downward, laterally, and the like thereof. In anembodiment, and without limitation, the plurality of flight controllersmay include one or more neural networks that assign a weighted value toa transmitted datum. For example, and without limitation, a weightedvalue may be assigned as a function of one or more signals denoting thata flight component is malfunctioning and/or in a failure state.

Still referring to FIG. 9 , the plurality of flight controllers mayinclude a master bus controller. As used in this disclosure a “masterbus controller” is one or more devices and/or components that areconnected to a bus to initiate a direct memory access transaction,wherein a bus is one or more terminals in a bus architecture. Master buscontroller may communicate using synchronous and/or asynchronous buscontrol protocols. In an embodiment, master bus controller may includeflight controller 904. In another embodiment, master bus controller mayinclude one or more universal asynchronous receiver-transmitters (UART).For example, and without limitation, master bus controller may includeone or more bus architectures that allow a bus to initiate a directmemory access transaction from one or more buses in the busarchitectures. As a further non-limiting example, master bus controllermay include one or more peripheral devices and/or components tocommunicate with another peripheral device and/or component and/or themaster bus controller. In an embodiment, master bus controller may beconfigured to perform bus arbitration. As used in this disclosure “busarbitration” is method and/or scheme to prevent multiple buses fromattempting to communicate with and/or connect to master bus controller.For example and without limitation, bus arbitration may include one ormore schemes such as a small computer interface system, wherein a smallcomputer interface system is a set of standards for physical connectingand transferring data between peripheral devices and master buscontroller by defining commands, protocols, electrical, optical, and/orlogical interfaces. In an embodiment, master bus controller may receiveintermediate representation 912 and/or output language from logiccomponent 920, wherein output language may include one or moreanalog-to-digital conversions, low bit rate transmissions, messageencryptions, digital signals, binary signals, logic signals, analogsignals, and the like thereof described above in detail.

Still referring to FIG. 9 , master bus controller may communicate with aslave bus. As used in this disclosure a “slave bus” is one or moreperipheral devices and/or components that initiate a bus transfer. Forexample, and without limitation, slave bus may receive one or morecontrols and/or asymmetric communications from master bus controller,wherein slave bus transfers data stored to master bus controller. In anembodiment, and without limitation, slave bus may include one or moreinternal buses, such as but not limited to a/an internal data bus,memory bus, system bus, front-side bus, and the like thereof. In anotherembodiment, and without limitation, slave bus may include one or moreexternal buses such as external flight controllers, external computers,remote devices, printers, aircraft computer systems, flight controlsystems, and the like thereof.

In an embodiment, and still referring to FIG. 9 , control algorithm mayoptimize signal communication as a function of determining one or morediscrete timings. For example, and without limitation master buscontroller may synchronize timing of the segmented control algorithm byinjecting high priority timing signals on a bus of the master buscontrol. As used in this disclosure a “high priority timing signal” isinformation denoting that the information is important. For example, andwithout limitation, high priority timing signal may denote that asection of control algorithm is of high priority and should be analyzedand/or transmitted prior to any other sections being analyzed and/ortransmitted. In an embodiment, high priority timing signal may includeone or more priority packets. As used in this disclosure a “prioritypacket” is a formatted unit of data that is communicated between theplurality of flight controllers. For example, and without limitation,priority packet may denote that a section of control algorithm should beused and/or is of greater priority than other sections.

Still referring to FIG. 9 , flight controller 904 may also beimplemented using a “shared nothing” architecture in which data iscached at the worker, in an embodiment, this may enable scalability ofaircraft and/or computing device. Flight controller 904 may include adistributer flight controller. As used in this disclosure a “distributerflight controller” is a component that adjusts and/or controls aplurality of flight components as a function of a plurality of flightcontrollers. For example, distributer flight controller may include aflight controller that communicates with a plurality of additionalflight controllers and/or clusters of flight controllers. In anembodiment, distributed flight control may include one or more neuralnetworks. For example, neural network also known as an artificial neuralnetwork, is a network of “nodes,” or data structures having one or moreinputs, one or more outputs, and a function determining outputs based oninputs. Such nodes may be organized in a network, such as withoutlimitation a convolutional neural network, including an input layer ofnodes, one or more intermediate layers, and an output layer of nodes.Connections between nodes may be created via the process of “training”the network, in which elements from a training dataset are applied tothe input nodes, a suitable training algorithm (such asLevenberg-Marquardt, conjugate gradient, simulated annealing, or otheralgorithms) is then used to adjust the connections and weights betweennodes in adjacent layers of the neural network to produce the desiredvalues at the output nodes. This process is sometimes referred to asdeep learning.

Still referring to FIG. 9 , a node may include, without limitation aplurality of inputs x_(i) that may receive numerical values from inputsto a neural network containing the node and/or from other nodes. Nodemay perform a weighted sum of inputs using weights w_(i) that aremultiplied by respective inputs x_(i). Additionally or alternatively, abias b may be added to the weighted sum of the inputs such that anoffset is added to each unit in the neural network layer that isindependent of the input to the layer. The weighted sum may then beinput into a function φ, which may generate one or more outputs y.Weight w_(i) applied to an input x_(i) may indicate whether the input is“excitatory,” indicating that it has strong influence on the one or moreoutputs y, for instance by the corresponding weight having a largenumerical value, and/or a “inhibitory,” indicating it has a weak effectinfluence on the one more inputs y, for instance by the correspondingweight having a small numerical value. The values of weights w_(i) maybe determined by training a neural network using training data, whichmay be performed using any suitable process as described above. In anembodiment, and without limitation, a neural network may receivesemantic units as inputs and output vectors representing such semanticunits according to weights w_(i) that are derived using machine-learningprocesses as described in this disclosure.

Still referring to FIG. 9 , flight controller may include asub-controller 940. As used in this disclosure a “sub-controller” is acontroller and/or component that is part of a distributed controller asdescribed above; for instance, flight controller 904 may be and/orinclude a distributed flight controller made up of one or moresub-controllers. For example, and without limitation, sub-controller 940may include any controllers and/or components thereof that are similarto distributed flight controller and/or flight controller as describedabove. Sub-controller 940 may include any component of any flightcontroller as described above. Sub-controller 940 may be implemented inany manner suitable for implementation of a flight controller asdescribed above. As a further non-limiting example, sub-controller 940may include one or more processors, logic components and/or computingdevices capable of receiving, processing, and/or transmitting dataacross the distributed flight controller as described above. As afurther non-limiting example, sub-controller 940 may include acontroller that receives a signal from a first flight controller and/orfirst distributed flight controller component and transmits the signalto a plurality of additional sub-controllers and/or flight components.

Still referring to FIG. 9 , flight controller may include aco-controller 944. As used in this disclosure a “co-controller” is acontroller and/or component that joins flight controller 904 ascomponents and/or nodes of a distributer flight controller as describedabove. For example, and without limitation, co-controller 944 mayinclude one or more controllers and/or components that are similar toflight controller 904. As a further non-limiting example, co-controller944 may include any controller and/or component that joins flightcontroller 904 to distributer flight controller. As a furthernon-limiting example, co-controller 944 may include one or moreprocessors, logic components and/or computing devices capable ofreceiving, processing, and/or transmitting data to and/or from flightcontroller 904 to distributed flight control system. Co-controller 944may include any component of any flight controller as described above.Co-controller 944 may be implemented in any manner suitable forimplementation of a flight controller as described above.

In an embodiment, and with continued reference to FIG. 9 , flightcontroller 904 may be designed and/or configured to perform any method,method step, or sequence of method steps in any embodiment described inthis disclosure, in any order and with any degree of repetition. Forinstance, flight controller 904 may be configured to perform a singlestep or sequence repeatedly until a desired or commanded outcome isachieved; repetition of a step or a sequence of steps may be performediteratively and/or recursively using outputs of previous repetitions asinputs to subsequent repetitions, aggregating inputs and/or outputs ofrepetitions to produce an aggregate result, reduction or decrement ofone or more variables such as global variables, and/or division of alarger processing task into a set of iteratively addressed smallerprocessing tasks. Flight controller may perform any step or sequence ofsteps as described in this disclosure in parallel, such assimultaneously and/or substantially simultaneously performing a step twoor more times using two or more parallel threads, processor cores, orthe like; division of tasks between parallel threads and/or processesmay be performed according to any protocol suitable for division oftasks between iterations. Persons skilled in the art, upon reviewing theentirety of this disclosure, will be aware of various ways in whichsteps, sequences of steps, processing tasks, and/or data may besubdivided, shared, or otherwise dealt with using iteration, recursion,and/or parallel processing.

Referring now to FIG. 10 , an exemplary embodiment of a machine-learningmodule 1000 that may perform one or more machine-learning processes asdescribed in this disclosure is illustrated. Machine-learning module mayperform determinations, classification, and/or analysis steps, methods,processes, or the like as described in this disclosure using machinelearning processes. A “machine learning process,” as used in thisdisclosure, is a process that automatedly uses training data 1004 togenerate an algorithm that will be performed by a computingdevice/module to produce outputs 1008 given data provided as inputs1012; this is in contrast to a non-machine learning software programwhere the commands to be executed are determined in advance by a userand written in a programming language.

Still referring to FIG. 10 , “training data,” as used herein, is datacontaining correlations that a machine-learning process may use to modelrelationships between two or more categories of data elements. Forinstance, and without limitation, training data 1004 may include aplurality of data entries, each entry representing a set of dataelements that were recorded, received, and/or generated together; dataelements may be correlated by shared existence in a given data entry, byproximity in a given data entry, or the like. Multiple data entries intraining data 1004 may evince one or more trends in correlations betweencategories of data elements; for instance, and without limitation, ahigher value of a first data element belonging to a first category ofdata element may tend to correlate to a higher value of a second dataelement belonging to a second category of data element, indicating apossible proportional or other mathematical relationship linking valuesbelonging to the two categories. Multiple categories of data elementsmay be related in training data 1004 according to various correlations;correlations may indicate causative and/or predictive links betweencategories of data elements, which may be modeled as relationships suchas mathematical relationships by machine-learning processes as describedin further detail below. Training data 1004 may be formatted and/ororganized by categories of data elements, for instance by associatingdata elements with one or more descriptors corresponding to categoriesof data elements. As a non-limiting example, training data 1004 mayinclude data entered in standardized forms by persons or processes, suchthat entry of a given data element in a given field in a form may bemapped to one or more descriptors of categories. Elements in trainingdata 1004 may be linked to descriptors of categories by tags, tokens, orother data elements; for instance, and without limitation, training data1004 may be provided in fixed-length formats, formats linking positionsof data to categories such as comma-separated value (CSV) formats and/orself-describing formats such as extensible markup language (XML),JavaScript Object Notation (JSON), or the like, enabling processes ordevices to detect categories of data.

Alternatively or additionally, and continuing to refer to FIG. 10 ,training data 1004 may include one or more elements that are notcategorized; that is, training data 1004 may not be formatted or containdescriptors for some elements of data. Machine-learning algorithmsand/or other processes may sort training data 1004 according to one ormore categorizations using, for instance, natural language processingalgorithms, tokenization, detection of correlated values in raw data andthe like; categories may be generated using correlation and/or otherprocessing algorithms. As a non-limiting example, in a corpus of text,phrases making up a number “n” of compound words, such as nouns modifiedby other nouns, may be identified according to a statisticallysignificant prevalence of n-grams containing such words in a particularorder; such an n-gram may be categorized as an element of language suchas a “word” to be tracked similarly to single words, generating a newcategory as a result of statistical analysis. Similarly, in a data entryincluding some textual data, a person's name may be identified byreference to a list, dictionary, or other compendium of terms,permitting ad-hoc categorization by machine-learning algorithms, and/orautomated association of data in the data entry with descriptors or intoa given format. The ability to categorize data entries automatedly mayenable the same training data 1004 to be made applicable for two or moredistinct machine-learning algorithms as described in further detailbelow. Training data 1004 used by machine-learning module 1000 maycorrelate any input data as described in this disclosure to any outputdata as described in this disclosure. As a non-limiting illustrativeexample flight elements and/or pilot signals may be inputs, wherein anoutput may be an autonomous function.

Further referring to FIG. 10 , training data may be filtered, sorted,and/or selected using one or more supervised and/or unsupervisedmachine-learning processes and/or models as described in further detailbelow; such models may include without limitation a training dataclassifier 1016. Training data classifier 1016 may include a“classifier,” which as used in this disclosure is a machine-learningmodel as defined below, such as a mathematical model, neural net, orprogram generated by a machine learning algorithm known as a“classification algorithm,” as described in further detail below, thatsorts inputs into categories or bins of data, outputting the categoriesor bins of data and/or labels associated therewith. A classifier may beconfigured to output at least a datum that labels or otherwiseidentifies a set of data that are clustered together, found to be closeunder a distance metric as described below, or the like.Machine-learning module 1000 may generate a classifier using aclassification algorithm, defined as a processes whereby a computingdevice and/or any module and/or component operating thereon derives aclassifier from training data 1004. Classification may be performedusing, without limitation, linear classifiers such as without limitationlogistic regression and/or naive Bayes classifiers, nearest neighborclassifiers such as k-nearest neighbors classifiers, support vectormachines, least squares support vector machines, fisher's lineardiscriminant, quadratic classifiers, decision trees, boosted trees,random forest classifiers, learning vector quantization, and/or neuralnetwork-based classifiers. As a non-limiting example, training dataclassifier 416 may classify elements of training data to sub-categoriesof flight elements such as torques, forces, thrusts, directions, and thelike thereof.

Still referring to FIG. 10 , machine-learning module 1000 may beconfigured to perform a lazy-learning process 1020 and/or protocol,which may alternatively be referred to as a “lazy loading” or“call-when-needed” process and/or protocol, may be a process wherebymachine learning is conducted upon receipt of an input to be convertedto an output, by combining the input and training set to derive thealgorithm to be used to produce the output on demand. For instance, aninitial set of simulations may be performed to cover an initialheuristic and/or “first guess” at an output and/or relationship. As anon-limiting example, an initial heuristic may include a ranking ofassociations between inputs and elements of training data 1004.Heuristic may include selecting some number of highest-rankingassociations and/or training data 1004 elements. Lazy learning mayimplement any suitable lazy learning algorithm, including withoutlimitation a K-nearest neighbors algorithm, a lazy naive Bayesalgorithm, or the like; persons skilled in the art, upon reviewing theentirety of this disclosure, will be aware of various lazy-learningalgorithms that may be applied to generate outputs as described in thisdisclosure, including without limitation lazy learning applications ofmachine-learning algorithms as described in further detail below.

Alternatively or additionally, and with continued reference to FIG. 10 ,machine-learning processes as described in this disclosure may be usedto generate machine-learning models 1024. A “machine-learning model,” asused in this disclosure, is a mathematical and/or algorithmicrepresentation of a relationship between inputs and outputs, asgenerated using any machine-learning process including withoutlimitation any process as described above, and stored in memory; aninput is submitted to a machine-learning model 1024 once created, whichgenerates an output based on the relationship that was derived. Forinstance, and without limitation, a linear regression model, generatedusing a linear regression algorithm, may compute a linear combination ofinput data using coefficients derived during machine-learning processesto calculate an output datum. As a further non-limiting example, amachine-learning model 1024 may be generated by creating an artificialneural network, such as a convolutional neural network comprising aninput layer of nodes, one or more intermediate layers, and an outputlayer of nodes. Connections between nodes may be created via the processof “training” the network, in which elements from a training data 1004set are applied to the input nodes, a suitable training algorithm (suchas Levenberg-Marquardt, conjugate gradient, simulated annealing, orother algorithms) is then used to adjust the connections and weightsbetween nodes in adjacent layers of the neural network to produce thedesired values at the output nodes. This process is sometimes referredto as deep learning.

Still referring to FIG. 10 , machine-learning algorithms may include atleast a supervised machine-learning process 1028. At least a supervisedmachine-learning process 1028, as defined herein, include algorithmsthat receive a training set relating a number of inputs to a number ofoutputs, and seek to find one or more mathematical relations relatinginputs to outputs, where each of the one or more mathematical relationsis optimal according to some criterion specified to the algorithm usingsome scoring function. For instance, a supervised learning algorithm mayinclude flight elements and/or pilot signals as described above asinputs, autonomous functions as outputs, and a scoring functionrepresenting a desired form of relationship to be detected betweeninputs and outputs; scoring function may, for instance, seek to maximizethe probability that a given input and/or combination of elements inputsis associated with a given output to minimize the probability that agiven input is not associated with a given output. Scoring function maybe expressed as a risk function representing an “expected loss” of analgorithm relating inputs to outputs, where loss is computed as an errorfunction representing a degree to which a prediction generated by therelation is incorrect when compared to a given input-output pairprovided in training data 1004. Persons skilled in the art, uponreviewing the entirety of this disclosure, will be aware of variouspossible variations of at least a supervised machine-learning process1028 that may be used to determine relation between inputs and outputs.Supervised machine-learning processes may include classificationalgorithms as defined above.

Further referring to FIG. 10 , machine learning processes may include atleast an unsupervised machine-learning processes 1032. An unsupervisedmachine-learning process, as used herein, is a process that derivesinferences in datasets without regard to labels; as a result, anunsupervised machine-learning process may be free to discover anystructure, relationship, and/or correlation provided in the data.Unsupervised processes may not require a response variable; unsupervisedprocesses may be used to find interesting patterns and/or inferencesbetween variables, to determine a degree of correlation between two ormore variables, or the like.

Still referring to FIG. 10 , machine-learning module 1000 may bedesigned and configured to create a machine-learning model 1024 usingtechniques for development of linear regression models. Linearregression models may include ordinary least squares regression, whichaims to minimize the square of the difference between predicted outcomesand actual outcomes according to an appropriate norm for measuring sucha difference (e.g. a vector-space distance norm); coefficients of theresulting linear equation may be modified to improve minimization.Linear regression models may include ridge regression methods, where thefunction to be minimized includes the least-squares function plus termmultiplying the square of each coefficient by a scalar amount topenalize large coefficients. Linear regression models may include leastabsolute shrinkage and selection operator (LASSO) models, in which ridgeregression is combined with multiplying the least-squares term by afactor of 1 divided by double the number of samples. Linear regressionmodels may include a multi-task lasso model wherein the norm applied inthe least-squares term of the lasso model is the Frobenius normamounting to the square root of the sum of squares of all terms. Linearregression models may include the elastic net model, a multi-taskelastic net model, a least angle regression model, a LARS lasso model,an orthogonal matching pursuit model, a Bayesian regression model, alogistic regression model, a stochastic gradient descent model, aperceptron model, a passive aggressive algorithm, a robustnessregression model, a Huber regression model, or any other suitable modelthat may occur to persons skilled in the art upon reviewing the entiretyof this disclosure. Linear regression models may be generalized in anembodiment to polynomial regression models, whereby a polynomialequation (e.g. a quadratic, cubic or higher-order equation) providing abest predicted output/actual output fit is sought; similar methods tothose described above may be applied to minimize error functions, aswill be apparent to persons skilled in the art upon reviewing theentirety of this disclosure.

Continuing to refer to FIG. 10 , machine-learning algorithms mayinclude, without limitation, linear discriminant analysis.Machine-learning algorithm may include quadratic discriminate analysis.Machine-learning algorithms may include kernel ridge regression.Machine-learning algorithms may include support vector machines,including without limitation support vector classification-basedregression processes. Machine-learning algorithms may include stochasticgradient descent algorithms, including classification and regressionalgorithms based on stochastic gradient descent. Machine-learningalgorithms may include nearest neighbors algorithms. Machine-learningalgorithms may include Gaussian processes such as Gaussian ProcessRegression. Machine-learning algorithms may include cross-decompositionalgorithms, including partial least squares and/or canonical correlationanalysis. Machine-learning algorithms may include naive Bayes methods.Machine-learning algorithms may include algorithms based on decisiontrees, such as decision tree classification or regression algorithms.Machine-learning algorithms may include ensemble methods such as baggingmeta-estimator, forest of randomized tress, AdaBoost, gradient treeboosting, and/or voting classifier methods. Machine-learning algorithmsmay include neural net algorithms, including convolutional neural netprocesses.

It is to be noted that any one or more of the aspects and embodimentsdescribed herein may be conveniently implemented using one or moremachines (e.g., one or more computing devices that are utilized as auser computing device for an electronic document, one or more serverdevices, such as a document server, etc.) programmed according to theteachings of the present specification, as will be apparent to those ofordinary skill in the computer art. Appropriate software coding canreadily be prepared by skilled programmers based on the teachings of thepresent disclosure, as will be apparent to those of ordinary skill inthe software art. Aspects and implementations discussed above employingsoftware and/or software modules may also include appropriate hardwarefor assisting in the implementation of the machine executableinstructions of the software and/or software module.

Such software may be a computer program product that employs amachine-readable storage medium. A machine-readable storage medium maybe any medium that is capable of storing and/or encoding a sequence ofinstructions for execution by a machine (e.g., a computing device) andthat causes the machine to perform any one of the methodologies and/orembodiments described herein. Examples of a machine-readable storagemedium include, but are not limited to, a magnetic disk, an optical disc(e.g., CD, CD-R, DVD, DVD-R, etc.), a magneto-optical disk, a read-onlymemory “ROM” device, a random access memory “RAM” device, a magneticcard, an optical card, a solid-state memory device, an EPROM, an EEPROM,and any combinations thereof. A machine-readable medium, as used herein,is intended to include a single medium as well as a collection ofphysically separate media, such as, for example, a collection of compactdiscs or one or more hard disk drives in combination with a computermemory. As used herein, a machine-readable storage medium does notinclude transitory forms of signal transmission.

Such software may also include information (e.g., data) carried as adata signal on a data carrier, such as a carrier wave. For example,machine-executable information may be included as a data-carrying signalembodied in a data carrier in which the signal encodes a sequence ofinstruction, or portion thereof, for execution by a machine (e.g., acomputing device) and any related information (e.g., data structures anddata) that causes the machine to perform any one of the methodologiesand/or embodiments described herein.

Examples of a computing device include, but are not limited to, anelectronic book reading device, a computer workstation, a terminalcomputer, a server computer, a handheld device (e.g., a tablet computer,a smartphone, etc.), a web appliance, a network router, a networkswitch, a network bridge, any machine capable of executing a sequence ofinstructions that specify an action to be taken by that machine, and anycombinations thereof. In one example, a computing device may includeand/or be included in a kiosk.

FIG. 11 shows a diagrammatic representation of one embodiment of acomputing device in the exemplary form of a computer system 1100 withinwhich a set of instructions for causing a control system to perform anyone or more of the aspects and/or methodologies of the presentdisclosure may be executed. It is also contemplated that multiplecomputing devices may be utilized to implement a specially configuredset of instructions for causing one or more of the devices to performany one or more of the aspects and/or methodologies of the presentdisclosure. Computer system 1100 includes a processor 1104 and a memory1108 that communicate with each other, and with other components, via abus 1112. Bus 1112 may include any of several types of bus structuresincluding, but not limited to, a memory bus, a memory controller, aperipheral bus, a local bus, and any combinations thereof, using any ofa variety of bus architectures.

Processor 1104 may include any suitable processor, such as withoutlimitation a processor incorporating logical circuitry for performingarithmetic and logical operations, such as an arithmetic and logic unit(ALU), which may be regulated with a state machine and directed byoperational inputs from memory and/or sensors; processor 1104 may beorganized according to Von Neumann and/or Harvard architecture as anon-limiting example. Processor 1104 may include, incorporate, and/or beincorporated in, without limitation, a microcontroller, microprocessor,digital signal processor (DSP), Field Programmable Gate Array (FPGA),Complex Programmable Logic Device (CPLD), Graphical Processing Unit(GPU), general purpose GPU, Tensor Processing Unit (TPU), analog ormixed signal processor, Trusted Platform Module (TPM), a floating pointunit (FPU), and/or system on a chip (SoC).

Memory 1108 may include various components (e.g., machine-readablemedia) including, but not limited to, a random-access memory component,a read only component, and any combinations thereof. In one example, abasic input/output system 1116 (BIOS), including basic routines thathelp to transfer information between elements within computer system1100, such as during start-up, may be stored in memory 1108. Memory 1108may also include (e.g., stored on one or more machine-readable media)instructions (e.g., software) 1120 embodying any one or more of theaspects and/or methodologies of the present disclosure. In anotherexample, memory 1108 may further include any number of program modulesincluding, but not limited to, an operating system, one or moreapplication programs, other program modules, program data, and anycombinations thereof.

Computer system 1100 may also include a storage device 1124. Examples ofa storage device (e.g., storage device 1124) include, but are notlimited to, a hard disk drive, a magnetic disk drive, an optical discdrive in combination with an optical medium, a solid-state memorydevice, and any combinations thereof. Storage device 1124 may beconnected to bus 1112 by an appropriate interface (not shown). Exampleinterfaces include, but are not limited to, SCSI, advanced technologyattachment (ATA), serial ATA, universal serial bus (USB), IEEE 1394(FIREWIRE), and any combinations thereof. In one example, storage device1124 (or one or more components thereof) may be removably interfacedwith computer system 1100 (e.g., via an external port connector (notshown)). Particularly, storage device 1124 and an associatedmachine-readable medium 1128 may provide nonvolatile and/or volatilestorage of machine-readable instructions, data structures, programmodules, and/or other data for computer system 1100. In one example,software 1120 may reside, completely or partially, withinmachine-readable medium 1128. In another example, software 1120 mayreside, completely or partially, within processor 1104.

Computer system 1100 may also include an input device 1132. In oneexample, a user of computer system 1100 may enter commands and/or otherinformation into computer system 1100 via input device 1132. Examples ofan input device 1132 include, but are not limited to, an alpha-numericinput device (e.g., a keyboard), a pointing device, a joystick, agamepad, an audio input device (e.g., a microphone, a voice responsesystem, etc.), a cursor control device (e.g., a mouse), a touchpad, anoptical scanner, a video capture device (e.g., a still camera, a videocamera), a touchscreen, and any combinations thereof. Input device 1132may be interfaced to bus 1112 via any of a variety of interfaces (notshown) including, but not limited to, a serial interface, a parallelinterface, a game port, a USB interface, a FIREWIRE interface, a directinterface to bus 1112, and any combinations thereof. Input device 1132may include a touch screen interface that may be a part of or separatefrom display 1136, discussed further below. Input device 1132 may beutilized as a user selection device for selecting one or more graphicalrepresentations in a graphical interface as described above.

A user may also input commands and/or other information to computersystem 1100 via storage device 1124 (e.g., a removable disk drive, aflash drive, etc.) and/or network interface device 1140. A networkinterface device, such as network interface device 1140, may be utilizedfor connecting computer system 1100 to one or more of a variety ofnetworks, such as network 1144, and one or more remote devices 1148connected thereto. Examples of a network interface device include, butare not limited to, a network interface card (e.g., a mobile networkinterface card, a LAN card), a modem, and any combination thereof.Examples of a network include, but are not limited to, a wide areanetwork (e.g., the Internet, an enterprise network), a local areanetwork (e.g., a network associated with an office, a building, a campusor other relatively small geographic space), a telephone network, a datanetwork associated with a telephone/voice provider (e.g., a mobilecommunications provider data and/or voice network), a direct connectionbetween two computing devices, and any combinations thereof. A network,such as network 1144, may employ a wired and/or a wireless mode ofcommunication. In general, any network topology may be used. Information(e.g., data, software 1120, etc.) may be communicated to and/or fromcomputer system 1100 via network interface device 1140.

Computer system 1100 may further include a video display adapter 1152for communicating a displayable image to a display device, such asdisplay device 1136. Examples of a display device include, but are notlimited to, a liquid crystal display (LCD), a cathode ray tube (CRT), aplasma display, a light emitting diode (LED) display, and anycombinations thereof. Display adapter 1152 and display device 1136 maybe utilized in combination with processor 1104 to provide graphicalrepresentations of aspects of the present disclosure. In addition to adisplay device, computer system 1100 may include one or more otherperipheral output devices including, but not limited to, an audiospeaker, a printer, and any combinations thereof. Such peripheral outputdevices may be connected to bus 1112 via a peripheral interface 1156.Examples of a peripheral interface include, but are not limited to, aserial port, a USB connection, a FIREWIRE connection, a parallelconnection, and any combinations thereof.

The foregoing has been a detailed description of illustrativeembodiments of the invention. Various modifications and additions can bemade without departing from the spirit and scope of this invention.Features of each of the various embodiments described above may becombined with features of other described embodiments as appropriate inorder to provide a multiplicity of feature combinations in associatednew embodiments. Furthermore, while the foregoing describes a number ofseparate embodiments, what has been described herein is merelyillustrative of the application of the principles of the presentinvention. Additionally, although particular methods herein may beillustrated and/or described as being performed in a specific order, theordering is highly variable within ordinary skill to achieve methods andsystems according to the present disclosure. Accordingly, thisdescription is meant to be taken only by way of example, and not tootherwise limit the scope of this invention.

Exemplary embodiments have been disclosed above and illustrated in theaccompanying drawings. It will be understood by those skilled in the artthat various changes, omissions and additions may be made to that whichis specifically disclosed herein without departing from the spirit andscope of the present invention.

What is claimed is:
 1. A distributed control system with supplementalattitude adjustment, the system comprising: an aircraft control, theaircraft control located within an aircraft having an aircraft attitude;a plurality of flight components located within an aircraft having anaircraft attitude; a plurality of aircraft components communicativelyconnected to the plurality of flight components, wherein each aircraftcomponent of the plurality of aircraft components is configured to:receive, from a command sensor attached to the aircraft control, anaircraft command; and generate a response command directing the flightcomponents as a function of an aggregate attitude, wherein the aggregateattitude combines a supplemental attitude with the aircraft attitude. 2.The system of claim 1, further comprising an aircraft control component,the aircraft control component communicatively connected to the aircraftcontrol, the aircraft control component configured to: calculate thedisplacement of the aircraft control from a default position; comparethe displacement of the aircraft control against a first threshold; andtransmit an engagement datum to the command sensor indicating that theaircraft control is engaged if the displacement of the aircraft controlexceeds the first threshold.
 3. The system of claim 2, wherein theaircraft control component is further configured to: compare thedisplacement of the aircraft control against a second threshold, whereinthe second threshold is less than the first threshold; and transmit anengagement datum to the command sensor indicating that the aircraftcontrol is disengaged if the displacement of the aircraft control doesnot exceed the second threshold.
 4. The system of claim 1, wherein eachaircraft component of the plurality of aircraft components is configuredto generate the supplemental attitude as a function of an engagementdatum
 5. The system of claim 4, wherein generating the supplementalattitude further comprises: determining that the aircraft control isdisengaged; and choosing a position supplemental attitude as a functionof the determination.; and
 6. The system of claim 4, wherein generatingthe supplemental attitude further comprises: determining that theaircraft control is engaged; and choosing a velocity supplementalattitude as a function of the determination.
 7. The system of claim 6,wherein each of the plurality of aircraft components is furtherconfigured to determine the velocity supplemental attitude by: receivinga desired velocity, the desired velocity including a desired directionof movement; receiving an actual velocity from a velocity sensor; andgenerating a velocity supplemental attitude, comprising: calculating thedifference between the desired velocity and the actual velocity; andcalculating the part of the difference that is perpendicular to thedesired direction of movement.
 8. The system of claim 1, wherein theplurality of aircraft components comprises a first aircraft componentand a second aircraft component, the first aircraft component is furtherconfigured to: receive an alternate signal from the second aircraftcomponent; and command the flight component as a function of thealternate signal.
 9. The system of claim 8, wherein the first aircraftcomponent is further configured to transmit an outgoing signal to thesecond aircraft component, wherein the outgoing signal contains theaggregate attitude.
 10. The system of claim 1, wherein each aircraftcomponent of the plurality of aircraft components is configured todirect a flight component of a plurality of flight components to producea response command based on the aggregate attitude, wherein the flightcomponent of the plurality of flight components is attached to anaircraft component of a plurality of aircraft components and is furtherconfigured to: receive an alternate signal from a second aircraftcomponent of the at least an aircraft component; and command the flightcomponent of a plurality of flight components as a function of thealternate signal
 11. A method of distributed control with supplementalattitude adjustment, comprising: receiving, by a plurality of aircraftcomponents communicatively connected to a plurality of flightcomponents, the plurality of aircraft components and the plurality offlight components located within an aircraft having an aircraftattitude, an aircraft command, wherein the aircraft command is receivedfrom a command sensor attached to an aircraft control; generating, bythe plurality of aircraft components, a response command directing theflight components as a function of an aggregate attitude, wherein theaggregate attitude combines a supplemental attitude with the aircraftattitude.
 12. The method of claim 11, further comprising an aircraftcontrol component, the aircraft control component communicativelyconnected to an aircraft control, the aircraft control componentconfigured to: calculate the displacement of the aircraft control from adefault position; compare the displacement of the aircraft controlagainst a first threshold; and transmit an engagement datum to thecommand sensor indicating that the aircraft control is engaged if thedisplacement of the aircraft control exceeds the first threshold. 13.The method of claim 12, further comprising: comparing the displacementof the aircraft control against a second threshold, wherein the secondthreshold is less than the first threshold; and transmitting anengagement datum to the command sensor indicating that the aircraftcontrol is disengaged if the displacement of the aircraft control doesnot exceed the second threshold.
 14. The method of claim 11, furthercomprising generating the supplemental attitude as a function of anengagement datum
 15. The method of claim 14, wherein generating thesupplemental attitude further comprises: determining that an aircraftcontrol of the aircraft is disengaged; and choosing a positionsupplemental attitude as a function of the determination.; and
 16. Themethod of claim 14, wherein generating the supplemental attitude furthercomprises: determining that an aircraft control of the aircraft isengaged; and choosing a velocity supplemental attitude as a function ofthe determination.
 17. The method of claim 16, wherein determining thevelocity supplemental attitude further comprises: receiving a desiredvelocity, the desired velocity including a desired direction ofmovement; receiving an actual velocity from a velocity sensor; andgenerating a velocity supplemental attitude, comprising: calculating thedifference between the desired velocity and the actual velocity; andcalculating the part of the difference that is perpendicular to thedesired direction of movement.
 18. The method of claim 11, wherein theplurality of aircraft components comprises a first aircraft componentand a second aircraft component, and further comprising: receiving, atthe first aircraft component an alternate signal from the secondaircraft component; and commanding, by the first aircraft component, theflight component as a function of the alternate signal.
 19. The methodof claim 18 further comprises transmitting, by the first aircraftcomponent, an outgoing signal to the second aircraft component, whereinthe outgoing signal contains the aggregate attitude.
 20. The method ofclaim 11, further comprising commanding, by an aircraft component of theplurality of aircraft components, a flight component of a plurality offlight components to produce a response command based on the aggregateattitude, wherein the flight component of the plurality of flightcomponents is attached to an aircraft component of a plurality ofaircraft components and is further configured to: receive an alternatesignal from a second aircraft component of the at least an aircraftcomponent; and command the flight component of a plurality of flightcomponents as a function of the alternate signal